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diff --git a/chapters/background.tex b/chapters/background.tex
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+\startcomponent background
+
+\chapter{Background}
+
+aroistenaoirstenoiaresntoien
+
+\stopcomponent
diff --git a/chapters/conclusion.tex b/chapters/conclusion.tex
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+\chapter{Conclusion}
diff --git a/chapters/dynamic.tex b/chapters/dynamic.tex
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+\chapter{\ymhfw{} Dynamic Scheduling}
diff --git a/chapters/hls.tex b/chapters/hls.tex
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+\environment fonts_env
+\environment lsr_env
+
+\startcomponent hls
+\product main
+
+\def\slowdownOrig{27}
+\def\slowdownDiv{2}
+\def\areaIncr{1.1}
+
+\chapter[sec:hls]{High-Level Synthesis}
+
+\paragraph{Can you trust your high-level synthesis tool?} As latency, throughput, and energy
+efficiency become increasingly important, custom hardware accelerators are being designed for
+numerous applications.  Alas, designing these accelerators can be a tedious and error-prone process
+using a hardware description language (HDL) such as Verilog.  An attractive alternative is
+\emph{high-level synthesis} (HLS), in which hardware designs are automatically compiled from
+software written in a high-level language like C.  Modern HLS tools such as
+LegUp~\cite{canis11_legup}, Vivado HLS~\cite{xilinx20_vivad_high_synth}, Intel i++~\cite{intel_hls},
+and Bambu HLS~\cite{bambu_hls} promise designs with comparable performance and energy-efficiency to
+those hand-written in an HDL~\cite{homsirikamol+14, silexicahlshdl, 7818341}, while offering the
+convenient abstractions and rich ecosystems of software development.  But existing HLS tools cannot
+always guarantee that the hardware designs they produce are equivalent to the software they were
+given, and this undermines any reasoning conducted at the software level.
+
+Indeed, there are reasons to doubt that HLS tools actually \emph{do} always preserve equivalence.
+For instance, Vivado HLS has been shown to apply pipelining optimisations
+incorrectly\footnote{\goto{https://bit.ly/vivado-hls-pipeline-bug}[url(https://bit.ly/vivado-hls-pipeline-bug)]}
+or to silently generate wrong code should the programmer stray outside the fragment of C that it
+supports.\footnote{\goto{https://bit.ly/vivado-hls-pointer-bug}[url(https://bit.ly/vivado-hls-pointer-bug)]}
+Meanwhile, \cite{lidbury15_many_core_compil_fuzzin} had to abandon their attempt to fuzz-test
+Altera's (now Intel's) OpenCL compiler since it \quotation{either crashed or emitted an internal
+  compiler error} on so many of their test inputs.  More recently,
+\cite{herklotz21_empir_study_reliab_high_level_synth_tools} fuzz-tested three commercial HLS tools
+using Csmith~\cite{yang11_findin_under_bugs_c_compil}, and despite restricting the generated
+programs to the C fragment explicitly supported by all the tools, they still found that on average
+2.5\% of test-cases were compiled to designs that behaved incorrectly.
+
+\paragraph{Existing workarounds.} Aware of the reliability shortcomings of HLS tools, hardware
+designers routinely check the generated hardware for functional correctness. This is commonly done
+by simulating the generated design against a large test-bench. But unless the test-bench covers all
+inputs exhaustively -- which is often infeasible -- there is a risk that bugs remain.
+
+One alternative is to use \emph{translation validation}~\cite{pnueli98_trans} to prove equivalence
+between the input program and the output design. Translation validation has been successfully
+applied to several HLS
+optimisations~\cite{kim04_autom_fsmd,karfa06_formal_verif_method_sched_high_synth,chouksey20_verif_sched_condit_behav_high_level_synth,banerjee14_verif_code_motion_techn_using_value_propag,chouksey19_trans_valid_code_motion_trans_invol_loops}.
+Nevertheless, it is an expensive task, especially for large designs, and it must be repeated every
+time the compiler is invoked.  For example, the translation validation for Catapult
+C~\cite{mentor20_catap_high_level_synth} may require several rounds of expert
+`adjustments'~\cite[alternative=authoryear,right={, p.~3)}][slec_whitepaper] to the input C program
+before validation succeeds. And even when it succeeds, translation validation does not provide
+watertight guarantees unless the validator itself has been mechanically proven
+correct~\cite[tristan08_formal_verif_trans_valid], which has not been the case in HLS tools to date.
+
+Our position is that none of the above workarounds are necessary if the HLS tool can simply be
+trusted to work correctly.
+
+\paragraph{Our solution.} We have designed a new HLS tool in the Coq theorem prover and proved that
+any output design it produces always has the same behaviour as its input program. Our tool, called
+Vericert, is automatically extracted to an OCaml program from Coq, which ensures that the object of
+the proof is the same as the implementation of the tool. Vericert is built by extending the CompCert
+verified C compiler~\cite[leroy09_formal_verif_realis_compil] with a new hardware-specific
+intermediate language and a Verilog back end. It supports most C constructs, including integer
+operations, function calls (which are all inlined), local arrays, structs, unions, and general
+control-flow statements, but currently excludes support for case statements, function pointers,
+recursive function calls, non-32-bit integers, floats, and global variables.
+
+\paragraph{Contributions and Outline.} The contributions of this paper are as follows:
+
+\startitemize[]
+\item We present Vericert, the first mechanically verified HLS tool that compiles C to Verilog. In
+  \in{Section}[sec:hls:design], we describe the design of Vericert, including certain optimisations
+  related to memory accesses and division.
+\item We state the correctness theorem of Vericert with respect to an existing semantics for Verilog
+  due to \cite[authoryear][loow19_proof_trans_veril_devel_hol]. In \in{Section}[sec:hls:verilog], we
+  describe how we extended this semantics to make it suitable as an HLS target.  We also describe
+  how the Verilog semantics is integrated into CompCert's language execution model and its framework
+  for performing simulation proofs. A mapping of CompCert's infinite memory model onto a finite
+  Verilog array is also described.
+\item In \in{Section}[sec:hls:proof], we describe how we proved the correctness theorem. The proof
+  follows standard CompCert techniques -- forward simulations, intermediate specifications, and
+  determinism results -- but we encountered several challenges peculiar to our hardware-oriented
+  setting.  These include handling discrepancies between the byte-addressed memory assumed by the
+  input software and the word-addressed memory that we implement in the output hardware, different
+  handling of unsigned comparisons between C and Verilog, and carefully implementing memory reads
+  and writes so that these behave properly as a RAM in hardware.
+\item In \in{Section}[sec:hls:evaluation], we evaluate Vericert on the PolyBench/C benchmark
+  suite~\cite[polybench], and compare the performance of our generated hardware against an existing,
+  unverified HLS tool called LegUp~\cite[canis11_legup]. We show that Vericert generates hardware
+  that is \slowdownOrig$\times$ slower (\slowdownDiv$\times$ slower in the absence of division) and
+  \areaIncr$\times$ larger than that generated by LegUp. This performance gap can be largely
+  attributed to Vericert's current lack of support for instruction-level parallelism and the absence
+  of an efficient, pipelined division operator. We intend to close this gap in the future by
+  introducing (and verifying) HLS optimisations of our own, such as scheduling and memory analysis.
+  This section also reports on our campaign to fuzz-test Vericert using over a hundred thousand
+  random C programs generated by Csmith~\cite{yang11_findin_under_bugs_c_compil} in order to confirm
+  that its correctness theorem is watertight.
+\stopitemize
+
+\paragraph{Companion material.} Vericert is fully open source and available on GitHub at
+
+\startalignment[center]
+  \goto{\hyphenatedurl{https://github.com/ymherklotz/vericert}}[url(https://github.com/ymherklotz/vericert)].
+\stopalignment
+
+A snapshot of the Vericert development is also available in a Zenodo
+repository~\cite{yann_herklotz_2021_5093839}.
+
+\section[sec:hls:design]{Designing a Verified HLS Tool}
+
+This section describes the main architecture of the HLS tool, and the way in which the Verilog back
+end was added to CompCert.  This section also covers an example of converting a simple C program
+into hardware, expressed in the Verilog language.
+
+\subsection{Main Design Decisions}
+
+\paragraph{Choice of source language.} C was chosen as the source language as it remains the most
+common source language amongst production-quality HLS tools~\cite[canis11_legup,
+  xilinx20_vivad_high_synth, intel_hls, bambu_hls]. This, in turn, may be because it is
+\quotation{[t]he starting point for the vast majority of algorithms to be implemented in
+  hardware}~\cite{5522874}, lending a degree of practicality.  The availability of
+CompCert~\cite{leroy09_formal_verif_realis_compil} also provides a solid basis for formally verified
+C compilation.  We considered Bluespec~\cite{nikhil04_blues_system_veril}, but decided that although
+it \quotation{can be classed as a high-level language}~\cite{greaves_note}, it is too hardware-oriented to
+be suitable for traditional HLS.  We also considered using a language with built-in parallel
+constructs that map well to parallel hardware, such as occam~\cite{page91_compil_occam},
+Spatial~\cite{spatial} or Scala~\cite{chisel}.
+
+\paragraph{Choice of target language.} Verilog~\cite{06_ieee_stand_veril_hardw_descr_languag} is an
+HDL that can be synthesised into logic cells which can either be placed onto a field-programmable
+gate array (FPGA) or turned into an application-specific integrated circuit (ASIC).  Verilog was
+chosen as the output language for Vericert because it is one of the most popular HDLs and there
+already exist a few formal semantics for it that could be used as a
+target~\cite{loow19_verif_compil_verif_proces, meredith10_veril}.  Bluespec, previously ruled out as
+a source language, is another possible target and there exists a formally verified translation to
+circuits using
+K\^{o}ika~\cite{bourgeat20_essen_blues}.
+
+\paragraph{Choice of implementation language.} We chose Coq as the implementation language because
+of its mature support for code extraction; that is, its ability to generate OCaml programs directly
+from the definitions used in the theorems.  We note that other authors have had some success
+reasoning about the HLS process using other theorem provers such as Isabelle~\cite{ellis08}.
+CompCert~\cite{leroy09_formal_verif_realis_compil} was chosen as the front end because it has a well
+established framework for simulation proofs about intermediate languages, and it already provides a
+validated C parser~\cite{jourdan12_valid_lr_parser}.  The Vellvm
+framework~\cite{zhao12_formal_llvm_inter_repres_verif_progr_trans} was also considered because
+several existing HLS tools are already LLVM-based, but additional work would be required to support
+a high-level language like C as input.  The .NET framework has been used as a basis for other HLS
+tools, such as Kiwi~\cite{kiwi}, and LLHD~\cite{schuiki20_llhd} has been recently proposed as an
+intermediate language for hardware design, but neither are suitable for us because they lack formal
+semantics.
+
+\startplacefigure[title={Vericert as a Verilog back end to CompCert.}]
+  \hbox{\starttikzpicture [language/.style={fill=white,rounded corners=3pt,minimum height=7mm},
+    continuation/.style={},
+    linecount/.style={rounded corners=3pt,dashed}]
+    \fill[compcert,rounded corners=3pt] (-1,-0.5) rectangle (9.9,2);
+    \fill[formalhls,rounded corners=3pt] (-1,-1) rectangle (9.9,-2.4);
+    %\draw[linecount] (-0.95,-0.45) rectangle (3.6,1);
+    %\draw[linecount] (4,-0.45) rectangle (7.5,1);
+    \node[language] at (-0.3,0) (clight) {Clight};
+    \node[continuation] at (1,0) (conta) {$\cdots$};
+    \node[language] at (2.7,0) (cminor) {CminorSel};
+    \node[language] at (4.7,0) (rtl) {3AC};
+    \node[language] at (6.2,0) (ltl) {LTL};
+    \node[language,anchor=west] at (8.4,0) (aarch) {aarch64};
+    \node[language,anchor=west] at (8.4,0.8) (x86) {x86};
+    \node[continuation,anchor=west] at (8.4,1.4) (backs) {$\cdots$};
+    \node[continuation] at (7.3,0) (contb) {$\cdots$};
+    \node[language] at (4.7,-1.5) (htl) {HTL};
+    \node[language] at (6.7,-1.5) (verilog) {Verilog};
+    \node[anchor=west] at (-0.9,1.6) {\bold{CompCert}};
+    \node[anchor=west] at (-0.9,-1.4) {\bold{Vericert}};
+    %%\node[anchor=west] at (-0.9,0.7) {\small $\sim$ 27 kloc};
+    %%\node[anchor=west] at (4.1,0.7) {\small $\sim$ 46 kloc};
+    %%\node[anchor=west] at (2,-1.5) {\small $\sim$ 17 kloc};
+    \node[align=center] at (3.2,-2) {RAM\blank insertion};
+    \draw[->,thick] (clight) -- (conta);
+    \draw[->,thick] (conta) -- (cminor);
+    \draw[->,thick] (cminor) -- (rtl);
+    \draw[->,thick] (rtl) -- (ltl);
+    \draw[->,thick] (ltl) -- (contb);
+    \draw[->,thick] (contb) -- (aarch);
+    \draw[->,thick] (contb) to [out=0,in=200] (x86.west);
+    \draw[->,thick] (contb) to [out=0,in=190] (backs.west);
+    \draw[->,thick] (rtl) -- (htl);
+    \draw[->,thick] (htl) -- (verilog);
+    \draw[->,thick] (htl.west) to [out=180,in=150] (4,-2.2) to [out=330,in=270] (htl.south);
+  \stoptikzpicture}
+\stopplacefigure
+
+\paragraph{Architecture of Vericert.} The main work flow of Vericert is given in
+Fig.~\ref{fig:rtlbranch}, which shows those parts of the translation that are performed in CompCert,
+and those that have been added.  This includes translations to two new intermediate languages added
+in Vericert, HTL and Verilog, as well as an additional optimisation pass labelled as \quotation{RAM
+insertion}.
+
+\def\numcompcertlanguages{ten}
+
+CompCert translates Clight\footnote{A deterministic subset of C with pure expressions.} input into
+assembly output via a sequence of intermediate languages; we must decide which of these
+\numcompcertlanguages{} languages is the most suitable starting point for the HLS-specific
+translation stages.
+
+We select CompCert's three-address code (3AC)\footnote{This is known as register transfer language
+  (RTL) in the CompCert literature. `3AC' is used in this paper instead to avoid confusion with
+  register-transfer level (RTL), which is another name for the final hardware target of the HLS
+  tool.} as the starting point. Branching off \emph{before} this point (at CminorSel or earlier)
+denies CompCert the opportunity to perform optimisations such as constant propagation and dead-code
+elimination, which, despite being designed for software compilers, have been found useful in HLS
+tools as well~\cite{cong+11}. And if we branch off \emph{after} this point (at LTL or later) then
+CompCert has already performed register allocation to reduce the number of registers and spill some
+variables to the stack; this transformation is not required in HLS because there are many more
+registers available, and these should be used instead of RAM whenever possible.
+
+3AC is also attractive because it is the closest intermediate language to LLVM IR, which is used by
+several existing HLS compilers.  It has an unlimited number of pseudo-registers, and is represented
+as a control flow graph (CFG) where each instruction is a node with links to the instructions that
+can follow it. One difference between LLVM IR and 3AC is that 3AC includes operations that are
+specific to the chosen target architecture; we chose to target the x86\_32 back end because it
+generally produces relatively dense 3AC thanks to the availability of complex addressing modes.
+
+\subsection{An Introduction to Verilog}
+
+This section will introduce Verilog for readers who may not be familiar with the language,
+concentrating on the features that are used in the output of Vericert.  Verilog is a hardware
+description language (HDL) and is used to design hardware ranging from complete CPUs that are
+eventually produced as integrated circuits, to small application-specific accelerators that are
+placed on FPGAs.  Verilog is a popular language because it allows for fine-grained control over the
+hardware, and also provides high-level constructs to simplify development.  \goto{yannherklotz.com}[url(https://yannherklotz.com)]
+
+Verilog behaves quite differently to standard software programming languages due to it having to
+express the parallel nature of hardware.  The basic construct to achieve this is the always-block,
+which is a collection of assignments that are executed every time some event occurs.  In the case of
+Vericert, this event is either a positive (rising) or a negative (falling) clock edge.  All
+always-blocks triggering on the same event are executed in parallel. Always-blocks can also express
+control-flow using if-statements and case-statements.
+
+\startplacefigure[reference={fig:tutorial:state_machine},location=top]
+  \setupinterlinespace[line=2.8ex]
+  \startfloatcombination [nx=2, ny=1]
+    \startplacesubfigure
+      \startframedtext[width={0.55\textwidth},frame=off,offset=none,bodyfont=11pt]
+      \starthlverilog
+         module main(input rst, input y,
+                     input clk, output reg z);
+           reg tmp, state;
+           always @(posedge clk)
+             case (state)
+               1'b0: tmp <= y;
+               1'b1: begin tmp <= 1'b0;
+                           z <= tmp; end
+             endcase
+           always @(posedge clk)
+             if (rst) state <= 1'b0;
+             else case (state)
+               1'b0: if (y) state <= 1'b1;
+                     else state <= 1'b0;
+               1'b1: state <= 1'b0;
+             endcase
+         endmodule
+      \stophlverilog
+    \stopframedtext
+    \stopplacesubfigure
+    \startplacesubfigure
+    \hbox{\starttikzpicture
+      \node[draw,circle,inner sep=6pt,fill=red] (s0) at (0,0) {$S_{\mathit{start}} / \mono{x}$};
+      \node[draw,circle,inner sep=8pt] (s1) at (1.5,-3) {$S_{1} / \mono{1}$};
+      \node[draw,circle,inner sep=8pt] (s2) at (3,0) {$S_{0} / \mono{1}$};
+      \node (s2s) at ($(s2.west) + (-0.3,1)$) {\mono{00}};
+      \node (s2ss) at ($(s2.east) + (0.3,1)$) {\mono{1x}};
+      \draw[-{Latex[length=2mm,width=1.4mm]}] ($(s0.west) + (-0.3,1)$) to [out=0,in=120] (s0);
+      \draw[-{Latex[length=2mm,width=1.4mm]}] (s0)
+           to [out=-90,in=150] node[midway,left] {\mono{01}} (s1);
+      \draw[-{Latex[length=2mm,width=1.4mm]}] (s1)
+      to [out=80,in=220] node[midway,left] {\mono{xx}} (s2);
+      \draw[-{Latex[length=2mm,width=1.4mm]}] (s2)
+      to [out=260,in=50] node[midway,right] {\mono{01}} (s1);
+      \draw[-{Latex[length=2mm,width=1.4mm]}] (s2)
+      to [out=120,in=40] ($(s2.west) + (-0.3,0.7)$) to [out=220,in=170] (s2);
+      \draw[-{Latex[length=2mm,width=1.4mm]}] (s2)
+      to [out=60,in=130] ($(s2.east) + (0.3,0.7)$) to [out=310,in=10] (s2);
+      \stoptikzpicture}
+    \stopplacesubfigure
+  \stopfloatcombination
+\stopplacefigure
+
+A simple state machine can be implemented as shown in Fig.~\ref{fig:tutorial:state_machine}.  At
+every positive edge of the clock (\mono{clk}), both of the always-blocks will trigger
+simultaneously.  The first always-block controls the values in the register \mono{x} and the output
+\mono{z}, while the second always-block controls the next state the state machine should go to.
+When the \mono{state} is 0, \mono{tmp} will be assigned to the input \mono{y} using nonblocking
+assignment, denoted by \mono{<=}.  Nonblocking assignment assigns registers in parallel at the end
+of the clock cycle, rather than sequentially throughout the always-block. In the second
+always-block, the input \mono{y} will be checked, and if it's high it will move on to the next
+state, otherwise it will stay in the current state.  When \mono{state} is 1, the first always-block
+will reset the value of \mono{tmp} and then set \mono{z} to the original value of \mono{tmp}, since
+nonblocking assignment does not change its value until the end of the clock cycle.  Finally, the
+last always-block will set the state to 0 again.
+
+\startplacefigure[location=here,reference={hello}]
+  \startfloatcombination[nx=2,ny=2]
+    \startplacesubfigure[title={1}]
+      \externalfigure[hacker.jpg]
+    \stopplacesubfigure
+    \startplacesubfigure[title={2}]
+      \externalfigure[hacker.jpg]
+    \stopplacesubfigure
+    \startplacesubfigure[title={3}]
+      \externalfigure[hacker.jpg]
+    \stopplacesubfigure
+    \startplacesubfigure[]
+      \externalfigure[hacker.jpg]
+    \stopplacesubfigure
+  \stopfloatcombination
+\stopplacefigure
+
+\in{Figure}{b}[hello]
+
+%\begin{figure}
+%  \centering
+%  \begin{subfigure}[b]{0.3\linewidth}
+%    \begin{subfigure}[t]{1\linewidth}
+%\begin{minted}[fontsize=\footnotesize,linenos,xleftmargin=20pt]{c}
+%int main() {
+%    int x[2] = {3, 6};
+%    int i = 1;
+%    return x[i];
+%}
+%\end{minted}
+%      \caption{Example C code passed to Vericert.}\label{fig:accumulator_c}
+%    \end{subfigure}\\\vspace{3em}
+%    \begin{subfigure}[b]{1\linewidth}
+%\begin{minted}[fontsize=\footnotesize,linenos,xleftmargin=20pt]{c}
+%main() {
+%    x5 = 3
+%    int32[stack(0)] = x5
+%    x4 = 6
+%    int32[stack(4)] = x4
+%    x1 = 1
+%    x3 = stack(0) (int)
+%    x2 = int32[x3 + x1
+%               * 4 + 0]
+%    return x2
+%}
+%\end{minted}
+%      \caption{3AC produced by the CompCert front-end without any optimisations.}\label{fig:accumulator_rtl}
+%    \end{subfigure}
+%  \end{subfigure}\hfill%
+%  \begin{subfigure}[b]{0.65\linewidth}
+%\begin{minted}[fontsize=\tiny,linenos,xleftmargin=20pt]{verilog}
+%module main(reset, clk, finish, return_val);
+%  input [0:0] reset, clk;
+%  output reg [0:0] finish = 0;
+%  output reg [31:0] return_val = 0;
+%  reg [31:0] reg_3 = 0, addr = 0, d_in = 0, reg_5 = 0, wr_en = 0;
+%  reg [0:0] en = 0, u_en = 0;
+%  reg [31:0] state = 0, reg_2 = 0, reg_4 = 0, d_out = 0, reg_1 = 0;
+%  reg [31:0] stack [1:0];
+%  // RAM interface
+%  always @(negedge clk)
+%    if ({u_en != en}) begin
+%      if (wr_en) stack[addr] <= d_in;
+%      else d_out <= stack[addr];
+%      en <= u_en;
+%    end
+%  // Data-path
+%  always @(posedge clk)
+%    case (state)
+%      32'd11: reg_2 <= d_out;
+%      32'd8: reg_5 <= 32'd3;
+%      32'd7: begin u_en <= ( ~ u_en); wr_en <= 32'd1;
+%                   d_in <= reg_5; addr <= 32'd0; end
+%      32'd6: reg_4 <= 32'd6;
+%      32'd5: begin u_en <= ( ~ u_en); wr_en <= 32'd1;
+%                   d_in <= reg_4; addr <= 32'd1; end
+%      32'd4: reg_1 <= 32'd1;
+%      32'd3: reg_3 <= 32'd0;
+%      32'd2: begin u_en <= ( ~ u_en); wr_en <= 32'd0;
+%                   addr <= {{{reg_3 + 32'd0} + {reg_1 * 32'd4}} / 32'd4}; end
+%      32'd1: begin finish = 32'd1; return_val = reg_2; end
+%      default: ;
+%    endcase
+%  // Control logic
+%  always @(posedge clk)
+%    if ({reset == 32'd1}) state <= 32'd8;
+%    else case (state)
+%           32'd11: state <= 32'd1;        32'd4: state <= 32'd3;
+%           32'd8: state <= 32'd7;         32'd3: state <= 32'd2;
+%           32'd7: state <= 32'd6;         32'd2: state <= 32'd11;
+%           32'd6: state <= 32'd5;         32'd1: ;
+%           32'd5: state <= 32'd4;         default: ;
+%         endcase
+%endmodule
+%\end{minted}
+%\caption{Verilog produced by Vericert. It demonstrates the instantiation of the RAM (lines 9--15), the data-path (lines 16--32) and the control logic (lines 33--42).}\label{fig:accumulator_v}
+%\end{subfigure}
+%\caption{Translating a simple program from C to Verilog.}\label{fig:accumulator_c_rtl}
+%% \NR{Is the default in line 41 of (c) supposed to be empty?}\YH{Yep, that's how it's generated.}
+%\end{figure}
+
+\subsection{Translating C to Verilog by Example}
+Fig.~\ref{fig:accumulator_c_rtl} illustrates the translation of a simple program that stores and retrieves values from an array.
+In this section, we describe the stages of the Vericert translation, referring to this program as an example.
+
+\subsubsection{Translating C to 3AC}
+
+The first stage of the translation uses unmodified CompCert to transform the C input, shown in
+Fig.~\ref{fig:accumulator_c}, into a 3AC intermediate representation, shown in
+Fig.~\ref{fig:accumulator_rtl}.  As part of this translation, function inlining is performed on all
+functions, which allows us to support function calls without having to support the \mono{Icall} 3AC
+instruction.  Although the duplication of the function bodies caused by inlining can increase the
+area of the hardware, it can have a positive effect on latency and is therefore a common HLS
+optimisation~\cite{noronha17_rapid_fpga}. Inlining precludes support for recursive function calls,
+but this feature is not supported in most HLS tools anyway~\cite{davidthomas_asap16}.
+
+\subsubsection{Translating 3AC to HTL}
+
+The next translation is from 3AC to a new hardware translation language (HTL).  This involves going
+from a CFG representation of the computation to a finite state machine with data-path (FSMD)
+representation~\cite{hwang99_fsmd}. The core idea of the FSMD representation is that it separates
+the control flow from the operations on the memory and registers.  Hence, an HTL program consists of
+two maps from states to Verilog statements: the \emph{control logic} map, which expresses state
+transitions, and the \emph{data-path} map, which expresses computations.
+Fig.~\ref{fig:accumulator_diagram} shows the resulting FSMD architecture. The right-hand block is
+the control logic that computes the next state, while the left-hand block updates all the registers
+and RAM based on the current program state.
+
+The HTL language was mainly introduced to simplify the proof of translation from 3AC to Verilog, as
+these languages have very different semantics.  It serves as an intermediate language with similar
+semantics to 3AC at the top level, using maps to represents what to execute at every state, and
+similar semantics to Verilog at the lower level by already using Verilog statements instead of more
+abstract instructions.  Compared to plain Verilog, HTL is simpler to manipulate and analyse, thereby
+making it easier to prove optimisations like proper RAM insertion.
+
+%\begin{figure*}
+%  \centering
+%\definecolor{control}{HTML}{b3e2cd}
+%\definecolor{data}{HTML}{fdcdac}
+%\begin{tikzpicture}
+%  \begin{scope}[scale=1.15]
+%  \fill[control,fill opacity=1] (6.5,0) rectangle (12,5);
+%  \fill[data,fill opacity=1] (0,0) rectangle (5.5,5);
+%  \node at (1,4.7) {Data-path};
+%  \node at (7.5,4.7) {Control Logic};
+%
+%  \fill[white,rounded corners=10pt] (7,0.5) rectangle (11.5,2.2);
+%  \node at (8,2) {\footnotesize Next State FSM};
+%  \foreach \x in {8,...,2}
+%    {\pgfmathtruncatemacro{\y}{8-\x}%
+%      \node[draw,circle,inner sep=0,minimum size=10,scale=0.8] (s\x) at (7.5+\y/2,1.35) {\tiny \x};}
+%  \node[draw,circle,inner sep=0,minimum size=10,scale=0.8] (s1c) at (11,1.35) {\tiny 1};
+%  \node[draw,circle,inner sep=0,minimum size=13,scale=0.8] (s1) at (s1c) {};
+%  \foreach \x in {8,...,3}
+%    {\pgfmathtruncatemacro{\y}{\x-1}\draw[-{Latex[length=1mm,width=0.7mm]}] (s\x) -- (s\y);}
+%  \node[draw,circle,inner sep=0,minimum size=10,scale=0.8] (s11) at (10.5,0.9) {\tiny 11};
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (s2) -- (s11);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (s11) -- (s1);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (7.2,1.7) to [out=0,in=100] (s8);
+%
+%  \node[draw,fill=white] (nextstate) at (9.25,3) {\tiny Current State};
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] let \p1 = (nextstate) in
+%    (11.5,1.25) -| (11.75,\y1) -- (nextstate);
+%  \draw let \p1 = (nextstate) in (nextstate) -- (6,\y1) |- (6,1.5);
+%  \node[scale=0.5,rotate=60] at (7.5,0.75) {\mono{clk}};
+%  \node[scale=0.5,rotate=60] at (7.7,0.75) {\mono{rst}};
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (7.65,-0.5) -- (7.65,0.5);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (7.45,-0.5) -- (7.45,0.5);
+%
+%  \fill[white,rounded corners=10pt] (2,0.5) rectangle (5,3);
+%  \filldraw[fill=white] (0.25,0.5) rectangle (1.5,2.75);
+%  \node at (2.6,2.8) {\footnotesize Update};
+%  \node[align=center] at (0.875,2.55) {\footnotesize \mono{RAM}};
+%  \node[scale=0.5] at (4.7,1.5) {\mono{state}};
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (6,1.5) -- (5,1.5);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (6,1.5) -- (7,1.5);
+%  \node[scale=0.5,rotate=60] at (4.1,0.9) {\mono{finished}};
+%  \node[scale=0.5,rotate=60] at (3.9,0.95) {\mono{return\_val}};
+%  \node[scale=0.5,rotate=60] at (2.5,0.75) {\mono{clk}};
+%  \node[scale=0.5,rotate=60] at (2.7,0.75) {\mono{rst}};
+%
+%  \node[scale=0.5,right,inner sep=5pt] (ram1) at (2,2.1) {\mono{u\_en}};
+%  \node[scale=0.5,right,inner sep=5pt] (ram2) at (2,1.9) {\mono{wr\_en}};
+%  \node[scale=0.5,right,inner sep=5pt] (ram3) at (2,1.7) {\mono{addr}};
+%  \node[scale=0.5,right,inner sep=5pt] (ram4) at (2,1.5) {\mono{d\_in}};
+%  \node[scale=0.5,right,inner sep=5pt] (ram5) at (2,1.3) {\mono{d\_out}};
+%
+%  \node[scale=0.5,left,inner sep=5pt] (r1) at (1.5,2.1) {\mono{u\_en}};
+%  \node[scale=0.5,left,inner sep=5pt] (r2) at (1.5,1.9) {\mono{wr\_en}};
+%  \node[scale=0.5,left,inner sep=5pt] (r3) at (1.5,1.7) {\mono{addr}};
+%  \node[scale=0.5,left,inner sep=5pt] (r4) at (1.5,1.5) {\mono{d\_in}};
+%  \node[scale=0.5,left,inner sep=5pt] (r5) at (1.5,1.3) {\mono{d\_out}};
+%
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (ram1) -- (r1);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (ram2) -- (r2);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (ram3) -- (r3);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (ram4) -- (r4);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (r5) -- (ram5);
+%
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (4,0.5) -- (4,-0.5);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (3.75,0.5) -- (3.75,-0.5);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (2.45,-0.5) -- (2.45,0.5);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (2.65,-0.5) -- (2.65,0.5);
+%
+%  \foreach \x in {0,...,1}
+%  {\draw (0.25,1-0.25*\x) -- (1.5,1-0.25*\x); \node at (0.875,0.88-0.25*\x) {\tiny \x};}
+%
+%  %\node[scale=0.5] at (1.2,2.2) {\mono{wr\_en}};
+%  %\node[scale=0.5] at (1.2,2) {\mono{wr\_addr}};
+%  %\node[scale=0.5] at (1.2,1.8) {\mono{wr\_data}};
+%  %\node[scale=0.5] at (1.2,1.4) {\mono{r\_addr}};
+%  %\node[scale=0.5] at (1.2,1.2) {\mono{r\_data}};
+%  %
+%  %\node[scale=0.5] at (2.3,2.2) {\mono{wr\_en}};
+%  %\node[scale=0.5] at (2.3,2) {\mono{wr\_addr}};
+%  %\node[scale=0.5] at (2.3,1.8) {\mono{wr\_data}};
+%  %\node[scale=0.5] at (2.3,1.4) {\mono{r\_addr}};
+%  %\node[scale=0.5] at (2.3,1.2) {\mono{r\_data}};
+%  %
+%  %\draw[-{Latex[length=1mm,width=0.7mm]}] (2,2.2) -- (1.5,2.2);
+%  %\draw[-{Latex[length=1mm,width=0.7mm]}] (2,2) -- (1.5,2);
+%  %\draw[-{Latex[length=1mm,width=0.7mm]}] (2,1.8) -- (1.5,1.8);
+%  %\draw[-{Latex[length=1mm,width=0.7mm]}] (2,1.4) -- (1.5,1.4);
+%  %\draw[-{Latex[length=1mm,width=0.7mm]}] (1.5,1.2) -- (2,1.2);
+%
+%  \filldraw[fill=white] (2.8,3.25) rectangle (4.2,4.75);
+%  \node at (3.5,4.55) {\footnotesize \mono{Registers}};
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (2,2.4) -| (1.75,4) -- (2.8,4);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (4.2,4) -- (5.25,4) |- (5,2.4);
+%  \draw[-{Latex[length=1mm,width=0.7mm]}] (5.25,2.4) -- (6.2,2.4) |- (7,1.8);
+%
+%  \node[scale=0.5] at (3.5,4.2) {\mono{reg\_1}};
+%  \node[scale=0.5] at (3.5,4) {\mono{reg\_2}};
+%  \node[scale=0.5] at (3.5,3.8) {\mono{reg\_3}};
+%  \node[scale=0.5] at (3.5,3.6) {\mono{reg\_4}};
+%  \node[scale=0.5] at (3.5,3.4) {\mono{reg\_5}};
+%\end{scope}
+%\end{tikzpicture}
+%  \Description{Diagram displaying the data-path and its internal modules, as well as the control logic and its state machine.}
+%  \caption{The FSMD for the example shown in Fig.~\ref{fig:accumulator_c_rtl}, split into a data-path and control logic for the next state calculation.  The Update block takes the current state, current values of all registers and at most one value stored in the RAM, and calculates a new value that can either be stored back in the RAM or in a register.}\label{fig:accumulator_diagram}
+%\end{figure*}
+
+\paragraph{Translating memory} Typically, HLS-generated hardware consists of a sea of registers and
+RAMs.  This memory view is very different from the C memory model, so we perform the following
+translation from CompCert's abstract memory model to a concrete RAM.  Variables that do not have
+their address taken are kept in registers, which correspond to the registers in 3AC.  All
+address-taken variables, arrays, and structs are kept in RAM.  The stack of the main function
+becomes an unpacked array of 32-bit integers representing the RAM block.  Any loads and stores are
+temporarily translated to direct accesses to this array, where each address has its offset removed
+and is divided by four.  In a separate HTL-to-HTL conversion, these direct accesses are then
+translated to proper loads and stores that use a RAM interface to communicate with the RAM, shown on
+lines 21, 24 and 28 of Fig.~\ref{fig:accumulator_v}.  This pass inserts a RAM block with the
+interface around the unpacked array.  Without this interface and without the RAM block, the
+synthesis tool processing the Verilog hardware description would not identify the array as a RAM,
+and would instead implement it using many registers.  This interface is shown on lines 9--15 in the
+Verilog code in Fig.~\ref{fig:accumulator_v}.  A high-level overview of the architecture and of the
+RAM interface can be seen in Fig.~\ref{fig:accumulator_diagram}.
+
+\paragraph{Translating instructions}
+
+Most 3AC instructions correspond to hardware constructs.  For example, line 2 in
+Fig.~\ref{fig:accumulator_rtl} shows a 32-bit register \mono{x5} being initialised to 3, after which
+the control flow moves execution to line 3. This initialisation is also encoded in the Verilog
+generated from HTL at state 8 in both the control logic and data-path always-blocks, shown at lines
+33 and 16 respectively in Fig.~\ref{fig:accumulator_v}.  Simple operator instructions are translated
+in a similar way.  For example, the add instruction is just translated to the built-in add operator,
+similarly for the multiply operator.  All 32-bit instructions can be translated in this way, but
+some special instructions require extra care. One such instruction is the \mono{Oshrximm}
+instruction, which is discussed further in Section~\ref{sec:algorithm:optimisation:oshrximm}.
+Another is the \mono{Oshldimm} instruction, which is a left rotate instruction that has no Verilog
+equivalent and therefore has to be implemented in terms of other operations and proven to be
+equivalent.  The only 32-bit instructions that we do not translate are case-statements
+(\mono{Ijumptable}) and those instructions related to function calls (\mono{Icall}, \mono{Ibuiltin},
+and \mono{Itailcall}), because we enable inlining by default.
+
+\subsubsection{Translating HTL to Verilog}
+
+Finally, we have to translate the HTL code into proper Verilog.  The challenge here is to translate
+our FSMD representation into a Verilog AST.  However, as all the instructions in HTL are already
+expressed as Verilog statements, only the top-level data-path and control logic maps need to be
+translated to valid Verilog case-statements.  We also require declarations for all the variables in
+the program, as well as declarations of the inputs and outputs to the module, so that the module can
+be used inside a larger hardware design.  In addition to translating the maps of Verilog statements,
+an always-block that will behave like the RAM also has to be created, which is only modelled
+abstractly at the HTL level.  Fig.~\ref{fig:accumulator_v} shows the final Verilog output that is
+generated for our example.
+
+Although this translation seems quite straight\-forward, proving that this translation is correct is
+complex.  All the implicit assumptions that were made in HTL need to be translated explicitly to
+Verilog statements and it needs to be shown that these explicit behaviours are equivalent to the
+assumptions made in the HTL semantics.  One main example of this is proving that the specification
+of the RAM in HTL does indeed behave in the same as its Verilog implementation.  We discuss these
+proofs in upcoming sections.
+
+\subsection{Optimisations}
+
+Although we would not claim that Vericert is a proper `optimising' HLS compiler yet, we have
+nonetheless made several design choices that aim to improve the quality of the hardware designs it
+produces.
+
+\subsubsection{Byte- and Word-Addressable Memories}
+
+One big difference between C and Verilog is how memory is represented.  Although Verilog arrays use
+similar syntax to C arrays, they must be treated quite differently. To make loads and stores as
+efficient as possible, the RAM needs to be word-addressable, which means that an entire integer can
+be loaded or stored in one clock cycle.  However, the memory model that CompCert uses for its
+intermediate languages is byte-addre\-ssa\-ble~\cite{blazy05_formal_verif_memor_model_c}.  If a
+byte-addressable memory was used in the target hardware, which is closer to CompCert's memory model,
+then a load and store would instead take four clock cycles, because a RAM can only perform one read
+and write per clock cycle.  It therefore has to be proven that the byte-addressable memory behaves
+in the same way as the word-addressable memory in hardware.  Any modifications of the bytes in the
+CompCert memory model also have to be shown to modify the word-addressable memory in the same way.
+Since only integer loads and stores are currently supported in Vericert, it follows that the
+addresses given to the loads and stores will be multiples of four.  Translating from byte-addressed
+memory to word-addressed memory can then be done by dividing the address by four.
+
+\subsubsection[sec:hls:algorithm:optimisation:ram]{Implementation of RAM Interface}
+
+The simplest way to implement loads and stores in Vericert would be to access the Verilog array
+directly from within the data-path (i.e., inside the always-block on lines 16--32 of
+Fig.~\ref{fig:accumulator_v}). This would be correct, but when a Verilog array is accessed at
+several program points, the synthesis tool is unlikely to detect that it can be implemented as a RAM
+block, and will resort to using lots of registers instead, ruining the circuit's area and
+performance.  To avert this, we arrange that the data-path does not access memory directly, but
+simply sets the address it wishes to access and then toggles the \mono{u\_en} flag. This activates
+the RAM interface (lines 9--15 of Fig.~\ref{fig:accumulator_v}) on the next falling clock edge,
+which performs the requested load or store. By factoring all the memory accesses out into a separate
+interface, we ensure that the underlying array is only accessed from a single program point in the
+Verilog code, and thus ensure that the synthesis tool will correctly infer a RAM
+block.\footnote{Interestingly, the Verilog code shown for the RAM interface must not be modified,
+  because the synthesis tool will only generate a RAM when the code matches a small set of specific
+  patterns.}
+
+Therefore, an extra compiler pass is added from HTL to HTL to extract all the direct accesses to the
+Verilog array and replace them by signals that access the RAM interface in a separate
+always-block. The translation is performed by going through all the instructions and replacing each
+load and store expression in turn.  Stores can simply be replaced by the necessary wires
+directly. Loads are a little more subtle: loads that use the RAM interface take two clock cycles
+where a direct load from an array takes only one, so this pass inserts an extra state after each
+load.
+
+There are two interesting parts to the inserted RAM interface.  Firstly, the memory updates are
+triggered on the negative (falling) edge of the clock, out of phase with the rest of the design
+which is triggered on the positive (rising) edge of the clock.  The advantage of this is that
+instead of loads and stores taking three clock cycles and two clock cycles respectively, they only
+take two clock cycles and one clock cycle instead, greatly improving their performance.  Using the
+negative edge of the clock is widely supported by synthesis tools, and does not affect the maximum
+frequency of the final design.
+
+Secondly, the logic in the enable signal of the RAM (\mono{en != u\_en}) is also atypical in
+hardware designs.  Enable signals are normally manually controlled and inserted into the appropriate
+states, by using a check like the following in the RAM: \mono{en == 1}.  This means that the RAM
+only turns on when the enable signal is set.  However, to make the proof simpler and avoid reasoning
+about possible side effects introduced by the RAM being enabled but not used, a RAM which disables
+itself after every use would be ideal.  One method for implementing this would be to insert an extra
+state after each load or store that disables the RAM, but this extra state would eliminate the speed
+advantage of the negative-edge-triggered RAM. Another method would be to determine the next state
+after each load or store and disable the RAM in that state, but this could quickly become
+complicated, especially in the case where the next state also contains a memory operation, and hence
+the disable signal should not be added. The method we ultimately chose was to have the RAM become
+enabled not when the enable signal is high, but when it \emph{toggles} its value.  This can be
+arranged by keeping track of the old value of the enable signal in \mono{en} and comparing it to the
+current value \mono{u\_en} set by the data-path.  When the values are different, the RAM gets
+enabled, and then \mono{en} is set to the value of \mono{u\_en}. This ensures that the RAM will
+always be disabled straight after it was used, without having to insert or modify any other states.
+
+%\begin{figure}
+%  \centering
+%  \begin{subfigure}[b]{0.48\linewidth}
+%    \begin{tikztimingtable}[timing/d/background/.style={fill=white}]
+%      \small clk & 2L 3{6C} \\
+%      \small u\_en & 2D{u\_en} 18D{$\overline{\text{u\_en}}$}\\
+%      \small addr & 2U 18D{3} \\
+%      \small wr\_en & 2U 18L \\
+%      \small en & 8D{u\_en} 12D{$\overline{\text{u\_en}}$}\\
+%      \small d\_out & 8U 12D{0xDEADBEEF} \\
+%      \small r & 14U 6D{0xDEADBEEF} \\
+%      \extracode
+%      \node[help lines] at (2,2.25) {\tiny 1};
+%      \node[help lines] at (8,2.25) {\tiny 2};
+%      \node[help lines] at (14,2.25) {\tiny 3};
+%      \begin{pgfonlayer}{background}
+%        \vertlines[help lines]{2,8,14}
+%      \end{pgfonlayer}
+%    \end{tikztimingtable}
+%    \caption{Timing diagram for loads. At time 1, the \mono{u\_en} signal is toggled to enable the RAM. At time 2, \mono{d\_out} is set to the value stored at the address in the RAM, which is finally assigned to the register \mono{r} at time 3.}\label{fig:ram_load}
+%  \end{subfigure}\hfill%
+%  \begin{subfigure}[b]{0.48\linewidth}
+%    \begin{tikztimingtable}[timing/d/background/.style={fill=white}]
+%      \small clk & 2L 2{7C} \\
+%      \small u\_en & 2D{u\_en} 14D{$\overline{\text{u\_en}}$}\\
+%      \small addr & 2U 14D{3} \\
+%      \small wr\_en & 2U 14H \\
+%      \small d\_in & 2U 14D{0xDEADBEEF} \\
+%      \small en & 9D{u\_en} 7D{$\overline{\text{u\_en}}$}\\
+%      \small stack[addr] & 9U 7D{0xDEADBEEF} \\
+%      \extracode
+%      \node[help lines] at (2,2.25) {\tiny 1};
+%      \node[help lines] at (9,2.25) {\tiny 2};
+%      \begin{pgfonlayer}{background}
+%        \vertlines[help lines]{2,9}
+%      \end{pgfonlayer}
+%    \end{tikztimingtable}
+%    \caption{Timing diagram for stores. At time 1, the \mono{u\_en} signal is toggled to enable the RAM, and the address \mono{addr} and the data to store \mono{d\_in} are set. On the negative edge at time 2, the data is stored into the RAM.}\label{fig:ram_store}
+%  \end{subfigure}
+%  \Description{Timing diagrams of loads and stores, showing which signals are modified at which time step.}
+%  \caption{Timing diagrams showing the execution of loads and stores over multiple clock cycles.}\label{fig:ram_load_store}
+%\end{figure}
+
+Fig.~\ref{fig:ram_load_store} gives an example of how the RAM interface behaves when values are
+loaded and stored.
+
+\subsubsection[sec:hls:algorithm:optimisation:oshrximm]{Implementing the \mono{Oshrximm}
+  Instruction}
+
+Many of the CompCert instructions map well to hardware, but \mono{Oshrximm} (efficient signed
+division by a power of two using a logical shift) is expensive if implemented na\"ively. The problem
+is that in CompCert it is specified as a signed division: (where $x, y \in \mathbb{Z}$,
+$0 \leq y < 31$, and $-2^{31} \leq x < 2^{31}$) and instantiating divider circuits in hardware is
+well known to cripple performance. Moreover, since Vericert requires the result of a divide
+operation to be ready within a single clock cycle, the divide circuit needs to be entirely
+combinational. This is inefficient in terms of area, but also in terms of latency, because it means
+that the maximum frequency of the hardware must be reduced dramatically so that the divide circuit
+has enough time to finish.  It should therefore be implemented using a sequence of shifts.
+
+CompCert eventually performs a translation from this representation into assembly code which uses
+shifts to implement the division, however, the specification of the instruction in 3AC itself still
+uses division instead of shifts, meaning this proof of the translation cannot be reused.  In
+Vericert, the equivalence of the representation in terms of divisions and shifts is proven over the
+integers and the specification, thereby making it simpler to prove the correctness of the Verilog
+implementation in terms of shifts.
+
+\section[title={A Formal Semantics for Verilog},reference={sec:verilog}]
+
+This section describes the Verilog semantics that was chosen for the target language, including the
+changes that were made to the semantics to make it a suitable HLS target. The Verilog standard is
+quite large~, but the syntax and semantics can be reduced to a small subset that needs to
+target. This section also describes how 's representation of memory differs from 's memory model.
+
+The Verilog semantics we use is ported to Coq from a semantics written in HOL4 by and used to prove
+the translation from HOL4 to Verilog~. This semantics is quite practical as it is restricted to a
+small subset of Verilog, which can nonetheless be used to model the hardware constructs required for
+HLS. The main features that are excluded are continuous assignment and combinational always-blocks;
+these are modelled in other semantics such as that by~.
+
+The semantics of Verilog differs from regular programming languages, as it is used to describe
+hardware directly, which is inherently parallel, rather than an algorithm, which is usually
+sequential. The main construct in Verilog is the always-block. A module can contain multiple
+always-blocks, all of which run in parallel. These always-blocks further contain statements such as
+if-statements or assignments to variables. We support only {\em synchronous} logic, which means that
+the always-block is triggered on (and only on) the positive or negative edge of a clock signal.
+
+The semantics combines the big-step and small-step styles. The overall execution of the hardware is
+described using a small-step semantics, with one small step per clock cycle; this is appropriate
+because hardware is routinely designed to run for an unlimited number of clock cycles and the
+big-step style is ill-suited to describing infinite executions. Then, within each clock cycle, a
+big-step semantics is used to execute all the statements. An example of a rule for executing an
+always-block that is triggered at the positive edge of the clock is shown below, where $\Sigma$ is
+the state of the registers in the module and $s$ is the statement inside the always-block:
+
+%\startformula \inferrule[Always]{(\Sigma, s)\downarrow_{\text{stmnt}} \Sigma'}{(\Sigma, \yhkeyword{always @(posedge clk) } s) \downarrow_{\text{always}^{+}} \Sigma'} \stopformula
+
+This rule says that assuming the statement $s$ in the always-block runs with state $\Sigma$ and
+produces the new state $\Sigma'$, the always-block will result in the same final state.
+
+Two types of assignments are supported in always-blocks: nonblocking and blocking
+assignment. Nonblocking assignments all take effect simultaneously at the end of the clock cycle,
+while blocking assignments happen instantly so that later assignments in the clock cycle can pick
+them up. To model both of these assignments, the state $\Sigma$ has to be split into two maps:
+$\Gamma$, which contains the current values of all variables and arrays, and $\Delta$, which
+contains the values that will be assigned at the end of the clock cycle. $\Sigma$ can therefore be
+defined as follows: $\Sigma = (\Gamma, \Delta)$. Nonblocking assignment can therefore be expressed
+as follows:
+
+%\startformula \inferrule[Nonblocking Reg]{\yhkeyword{name}\ d = \yhkeyword{OK}\ n \\ (\Gamma, e) \downarrow_{\text{expr}} v}{((\Gamma, \Delta), d\ \yhkeyword{ <= } e) \downarrow_{\text{stmnt}} (\Gamma, \Delta [n \mapsto v])}\\ \stopformula
+
+where assuming that $\downarrow_{\text{expr}}$ evaluates an expression $e$ to a value $v$, the
+nonblocking assignment $d\ \mono{ <= } e$ updates the future state of the variable $d$ with value
+$v$.
+
+Finally, the following rule dictates how the whole module runs in one clock cycle:
+
+%\startformula \inferrule[Module]{(\Gamma, \epsilon, \vec{m})\ \downarrow_{\text{module}} (\Gamma', \Delta')}{(\Gamma, \yhkeyword{module } \yhconstant{main} \yhkeyword{(...);}\ \vec{m}\ \yhkeyword{endmodule}) \downarrow_{\text{program}} (\Gamma'\ //\ \Delta')} \stopformula
+%
+where $\Gamma$ is the initial state of all the variables, $\epsilon$ is the empty map because the
+$\Delta$ map is assumed to be empty at the start of the clock cycle, and $\vec{m}$ is a list of
+variable declarations and always-blocks that $\downarrow_{\text{module}}$ evaluates sequentially to
+obtain $(\Gamma', \Delta')$. The final state is obtained by merging these maps using the $//$
+operator, which gives priority to the right-hand operand in a conflict. This rule ensures that the
+nonblocking assignments overwrite at the end of the clock cycle any blocking assignments made during
+the cycle.
+
+\subsection[title={Changes to the
+Semantics},reference={changes-to-the-semantics}]
+
+Five changes were made to the semantics proposed by to make it suitable as an HLS target.
+
+\subsubsection[title={Adding array
+support},reference={adding-array-support}]
+
+The main change is the addition of support for arrays, which are needed to model RAM in Verilog. RAM
+is needed to model the stack in C efficiently, without having to declare a variable for each
+possible stack location. Consider the following Verilog code:
+
+\starthlverilog
+reg [31:0] x[1:0];
+always @(posedge clk) begin x[0] = 1; x[1] <= 1; end
+\stophlverilog
+
+which modifies one array element using blocking assignment and then a second using nonblocking
+assignment. If the existing semantics were used to update the array, then during the merge, the
+entire array \type{x} from the nonblocking association map would replace the entire array from the
+blocking association map. This would replace \type{x[0]} with its original value and therefore
+behave incorrectly. Accordingly, we modified the maps so they record updates on a per-element
+basis. Our state $\Gamma$ is therefore further split up into $\Gamma_{r}$ for instantaneous updates
+to variables, and $\Gamma_{a}$ for instantaneous updates to arrays
+($\Gamma = (\Gamma_{r}, \Gamma_{a})$); $\Delta$ is split similarly
+($\Delta = (\Delta_{r}, \Delta_{a})$). The merge function then ensures that only the modified
+indices get updated when $\Gamma_{a}$ is merged with the nonblocking map equivalent $\Delta_{a}$.
+
+\subsubsection[adding-negative-edge-support]{Adding negative edge support}
+
+To reason about circuits that execute on the negative edge of the clock (such as our RAM interface
+described in Section~\goto{{[}sec:algorithm:optimisation:ram{]}}[sec:algorithm:optimisation:ram]),
+support for negative-edge-triggered always-blocks was added to the semantics. This is shown in the
+modifications of the {\sc Module} rule shown below:
+
+%\startformula \inferrule[Module]{(\Gamma, \epsilon, \vec{m})\ \downarrow_{\text{module}^{+}} (\Gamma', \Delta') \\ (\Gamma'\ //\ \Delta', \epsilon, \vec{m}) \downarrow_{\text{module}^{-}} (\Gamma'', \Delta'')}{(\Gamma, \yhkeyword{module}\ \yhconstant{main} \yhkeyword{(...);}\ \vec{m}\ \yhkeyword{endmodule}) \downarrow_{\text{program}} (\Gamma''\ //\ \Delta'')} \stopformula
+
+The main execution of the module $\downarrow_{\text{module}}$ is split into
+$\downarrow_{\text{module}^{+}}$ and $\downarrow_{\text{module}^{-}}$, which are rules that only
+execute always-blocks triggered at the positive and at the negative edge respectively. The
+positive-edge-triggered always-blocks are processed in the same way as in the original {\sc Module}
+rule. The output maps $\Gamma'$ and $\Delta'$ are then merged and passed as the blocking assignments
+map into the negative edge execution, so that all the blocking and nonblocking assignments are
+present. Finally, all the negative-edge-triggered always-blocks are processed and merged to give the
+final state.
+
+\subsubsection[adding-declarations]{Adding declarations}
+
+Explicit support for declaring inputs, outputs and internal variables was added to the semantics to
+make sure that the generated Verilog also contains the correct declarations. This adds some
+guarantees to the generated Verilog and ensures that it synthesises and simulates correctly.
+
+\subsubsection[removing-support-for-external-inputs-to-modules]{Removing support for external inputs
+  to modules}
+
+Support for receiving external inputs was removed from the semantics for simplicity, as these are
+not needed for an HLS target. The main module in Verilog models the main function in C, and since
+the inputs to a C function should not change during its execution, there is no need for external
+inputs for Verilog modules.
+
+\subsubsection[simplifying-representation-of-bitvectors]{Simplifying representation of bitvectors}
+
+Finally, we use 32-bit integers to represent bitvectors rather than arrays of booleans. This is
+because (currently) only supports types represented by 32 bits.
+
+\subsection[sec:verilog:integrating]{Integrating the Verilog Semantics into 's Model}
+
+%\startformula \begin{gathered}
+%      \inferrule[Step]{\Gamma_r[\mathit{rst}] = 0 \\ \Gamma_r[\mathit{fin}] = 0 \\ (m, (\Gamma_r, \Gamma_a))\ \downarrow_{\text{program}} (\Gamma_r', \Gamma_a')}{\yhconstant{State}\ \mathit{sf}\ m\ \ \Gamma_r[\sigma]\ \ \Gamma_r\ \Gamma_a \longrightarrow \yhconstant{State}\ \mathit{sf}\ m\ \ \Gamma_r'[\sigma]\ \ \Gamma_r'\ \Gamma_a'}\\
+%      %
+%      \inferrule[Finish]{\Gamma_r[\mathit{fin}] = 1}{\yhconstant{State}\ \mathit{sf}\ m\ \sigma\ \Gamma_r\ \Gamma_a \longrightarrow \yhconstant{Returnstate}\ \mathit{sf}\ \Gamma_r[ \mathit{ret}]}\\
+%      %
+%      \inferrule[Call]{ }{\yhconstant{Callstate}\ \mathit{sf}\ m\ \vec{r} \longrightarrow \yhconstant{State}\ \mathit{sf}\ m\ n\ ((\yhfunction{init\_params}\ \vec{r}\ a)[\sigma \mapsto n, \mathit{fin} \mapsto 0, \mathit{rst} \mapsto 0])\ \epsilon}\\
+%      %
+%      \inferrule[Return]{ }{\yhconstant{Returnstate}\ (\yhconstant{Stackframe}\ r\ m\ \mathit{pc}\ \Gamma_r\ \Gamma_a :: \mathit{sf})\ v \longrightarrow \yhconstant{State}\ \mathit{sf}\ m\ \mathit{pc}\ (\Gamma_{r} [ \sigma \mapsto \mathit{pc}, r \mapsto v ])\ \Gamma_{a}}
+%    \end{gathered} \stopformula
+
+The computation model defines a set of states through which execution passes. In this subsection, we
+explain how we extend our Verilog semantics with four special-purpose registers in order to
+integrate it into .
+
+executions pass through three main states:
+
+%\startdescription{\type{State} $\mathit{sf}$ $m$ $v$ $\Gamma_{r}$
+%$\Gamma_{a}$}
+%  The main state when executing a function, with stack frame
+%  $\mathit{sf}$, current module $m$, current state $v$ and variable
+%  states $\Gamma_{r}$ and $\Gamma_{a}$.
+%\stopdescription
+%
+%\startdescription{\type{Callstate} $\mathit{sf}$ $m$ $\vec{r}$}
+%  The state that is reached when a function is called, with the current
+%  stack frame $\mathit{sf}$, current module $m$ and arguments $\vec{r}$.
+%\stopdescription
+%
+%\startdescription{\type{Returnstate} $\mathit{sf}$ $v$}
+%  The state that is reached when a function returns back to the caller,
+%  with stack frame $\mathit{sf}$ and return value $v$.
+%\stopdescription
+%
+%To support this computational model, we extend the Verilog module we
+%generate with the following four registers and a RAM block:
+%
+%\startdescription{program counter}
+%  The program counter can be modelled using a register that keeps track
+%  of the state, denoted as $\sigma$.
+%\stopdescription
+%
+%\startdescription{function entry point}
+%  When a function is called, the entry point denotes the first
+%  instruction that will be executed. This can be modelled using a reset
+%  signal that sets the state accordingly, denoted as $\mathit{rst}$.
+%\stopdescription
+%
+%\startdescription{return value}
+%  The return value can be modelled by setting a finished flag to 1 when
+%  the result is ready, and putting the result into a 32-bit output
+%  register. These are denoted as $\mathit{fin}$ and $\mathit{ret}$
+%  respectively.
+%\stopdescription
+%
+%\startdescription{stack}
+%  The function stack can be modelled as a RAM block, which is
+%  implemented using an array in the module, and denoted as
+%  $\mathit{stk}$.
+%\stopdescription
+
+Fig.~\goto{{[}fig:inference_module{]}}[fig:inference_module] shows the inference rules for moving
+between the computational states. The first, {\sc Step}, is the normal rule of execution. It defines
+one step in the \type{State} state, assuming that the module is not being reset, that the finish
+state has not been reached yet, that the current and next state are $v$ and $v'$, and that the
+module runs from state $\Gamma$ to $\Gamma'$ using the {\sc Step} rule. The {\sc Finish} rule
+returns the final value of running the module and is applied when the $\mathit{fin}$ register is
+set; the return value is then taken from the $\mathit{ret}$ register.
+
+Note that there is no step from \type{State} to \type{Callstate}; this is because function calls are
+not supported, and it is therefore impossible in our semantics ever to reach a \type{Callstate}
+except for the initial call to main. So the {\sc Call} rule is only used at the very beginning of
+execution; likewise, the {\sc Return} rule is only matched for the final return value from the main
+function. Therefore, in addition to the rules shown in
+Fig.~\goto{{[}fig:inference_module{]}}[fig:inference_module], an initial state and final state need
+to be defined:
+
+%\startformula \begin{gathered}
+%  \inferrule[Initial]{\yhfunction{is\_internal}\ P.\mono{main}}{\yhfunction{initial\_state}\ (\yhconstant{Callstate}\ []\ P.\mono{main}\ [])}\qquad
+%  \inferrule[Final]{ }{\yhfunction{final\_state}\ (\yhconstant{Returnstate}\ []\ n)\ n}\end{gathered} \stopformula
+
+where the initial state is the \type{Callstate} with an empty stack frame and no arguments for the
+\type{main} function of program $P$, where this \type{main} function needs to be in the current
+translation unit. The final state results in the program output of value $n$ when reaching a
+\type{Returnstate} with an empty stack frame.
+
+\subsection[title={Memory Model},reference={sec:verilog:memory}]
+
+The Verilog semantics do not define a memory model for Verilog, as this is not needed for a hardware
+description language. There is no preexisting architecture that Verilog will produce; it can
+describe any memory layout that is needed. Instead of having specific semantics for memory, the
+semantics only needs to support the language features that can produce these different memory
+layouts, these being Verilog arrays.  We therefore define semantics for updating Verilog arrays
+using blocking and nonblocking assignment. We then have to prove that the C memory model that uses
+matches with the interpretation of arrays used in Verilog. The memory model is infinite, whereas our
+representation of arrays in Verilog is inherently finite. There have already been efforts to define
+a general finite memory model for all intermediate languages in , such as S~ or -TSO~, or keeping
+the intermediate languages intact and translate to a more concrete finite memory model in the back
+end, such as in ELF~. We also define such a translation from 's standard infinite memory model to
+finite arrays that can be represented in Verilog. There is therefore no more notion of an abstract
+memory model and all the interactions to memory are encoded in the hardware itself.
+
+This translation is represented in
+Fig.~\goto{{[}fig:memory_model_transl{]}}[fig:memory_model_transl].  defines a map from blocks to
+maps from memory addresses to memory contents. Each block represents an area in memory; for example,
+a block can represent a global variable or a stack for a function. As there are no global variables,
+the main stack can be assumed to be block 0, and this is the only block we translate. Meanwhile, our
+Verilog semantics defines two finite arrays of optional values, one for the blocking assignments map
+$\Gamma_{\rm a}$ and one for the nonblocking assignments map $\Delta_{\rm a}$. The optional values
+are present to ensure correct merging of the two association maps at the end of the clock cycle. The
+invariant used in the proofs is that block 0 should be equivalent to the merged representation of
+the $\Gamma_{\rm a}$ and $\Delta_{\rm a}$ maps.
+
+\section[sec:proof]{Correctness Proof}
+
+Now that the Verilog semantics have been adapted to the CompCert model, we are in a position to
+formally prove the correctness of our C-to-Verilog compilation. This section describes the main
+correctness theorem that was proven and the key ideas in the proof. The full Coq proof is available
+online~.
+
+\subsection[main-challenges-in-the-proof]{Main Challenges in the Proof}
+
+The proof of correctness of the Verilog back end is quite different from the usual proofs performed
+in CompCert, mainly because of the difference in the memory model and semantic differences between
+Verilog and CompCert's existing intermediate languages.
+
+\startitemize
+\item
+  As already mentioned in Section~\goto{{[}sec:verilog:memory{]}}[sec:verilog:memory], because the
+  memory model in our Verilog semantics is finite and concrete, but the CompCert memory model is
+  more abstract and infinite with additional bounds, the equivalence of these models needs to be
+  proven.  Moreover, our memory is word-addressed for efficiency reasons, whereas CompCert's memory
+  is byte-addressed.
+\item
+  Second, the Verilog semantics operates quite differently to the usual intermediate languages in
+  CompCert. All the CompCert intermediate languages use a map from control-flow nodes to
+  instructions. An instruction can therefore be selected using an abstract program
+  pointer. Meanwhile, in the Verilog semantics the whole design is executed at every clock cycle,
+  because hardware is inherently parallel. The program pointer is part of the design as well, not
+  just part of an abstract state. This makes the semantics of Verilog simpler, but comparing it to
+  the semantics of 3AC becomes more challenging, as one has to map the abstract notion of the state
+  to concrete values in registers.
+\stopitemize
+
+Together, these differences mean that translating 3AC directly to Verilog is infeasible, as the
+differences in the semantics are too large. Instead, HTL, which was introduced in
+Section~\goto{{[}sec:design{]}}[sec:design], bridges the gap in the semantics between the two
+languages. HTL still consists of maps, like many of the other CompCert languages, but each state
+corresponds to a Verilog statement.
+
+\subsection[formulating-the-correctness-theorem]{Formulating the Correctness Theorem}
+
+The main correctness theorem is analogous to that stated in ~: for all Clight source programs $C$,
+if the translation to the target Verilog code succeeds, $\mathit{Safe}(C)$ holds and the target
+Verilog has behaviour $B$ when simulated, then $C$ will have the same behaviour $B$.
+$\mathit{Safe}(C)$ means all observable behaviours of $C$ are safe, which can be defined as
+$\forall B,\ C \Downarrow B \implies B \in \mono{Safe}$. A behaviour is in \type{Safe} if it is
+either a final state (in the case of convergence) or divergent, but it cannot \quote{go
+  wrong}. (This means that the source program must not contain undefined behaviour.) In , a
+behaviour is also associated with a trace of I/O events, but since external function calls are not
+supported in , this trace will always be empty.
+
+Whenever the translation from $C$ succeeds and produces Verilog $V$, and all observable behaviours
+of $C$ are safe, then $V$ has behaviour $B$ only if $C$ has behaviour $B$.
+
+%\startformula \forall C, V, B,\quad \yhfunction{HLS} (C) = \yhconstant{OK} (V) \land \mathit{Safe}(C) \implies (V \Downarrow B \implies C \Downarrow B). \stopformula
+
+Why is this correctness theorem also the right one for HLS? It could be argued that hardware
+inherently runs forever and therefore does not produce a definitive final result. This would mean
+that the correctness theorem would probably be unhelpful with proving hardware correctness, as the
+behaviour would always be divergent. However, in practice, HLS does not normally produce the
+top-level of the design that needs to connect to other components, therefore needing to run
+forever. Rather, HLS often produces smaller components that take an input, execute, and then
+terminate with an answer. To start the execution of the hardware and to signal to the HLS component
+that the inputs are ready, the $\mathit{rst}$ signal is set and unset. Then, once the result is
+ready, the $\mathit{fin}$ signal is set and the result value is placed in $\mathit{ret}$. These
+signals are also present in the semantics of execution shown in
+Fig.~\goto{{[}fig:inference_module{]}}[fig:inference_module]. The correctness theorem therefore also
+uses these signals, and the proof shows that once the $\mathit{fin}$ flag is set, the value in
+$\mathit{ret}$ is correct according to the semantics of Verilog and Clight. Note that the compiler
+is allowed to fail and not produce any output; the correctness theorem only applies when the
+translation succeeds.
+
+How can we prove this theorem? First, note that the theorem is a \quote{backwards simulation} result
+(every target behaviour must also be a source behaviour), following the terminology used in the
+literature~.  The reverse direction (every source behaviour must also be a target behaviour) is not
+demanded because compilers are permitted to resolve any non-determinism present in their source
+programs. However, since Clight programs are all deterministic, as are the Verilog programs in the
+fragment we consider, we can actually reformulate the correctness theorem above as a forwards
+simulation result (following standard practice), which makes it easier to prove. To prove this
+forward simulation, it suffices to prove forward simulations between each pair of consecutive
+intermediate languages, as these results can be composed to prove the correctness of the whole HLS
+tool. The forward simulation from 3AC to HTL is stated in Lemma~\goto{{[}lemma:htl{]}}[lemma:htl]
+(Section~\goto{1.3}[sec:proof:3ac_htl]), the forward simulation for the RAM insertion is shown in
+Lemma~\goto{{[}lemma:htl_ram{]}}[lemma:htl_ram] (Section~\goto{1.4}[sec:proof:ram_insertion]), then
+the forward simulation between HTL and Verilog is shown in
+Lemma~\goto{{[}lemma:verilog{]}}[lemma:verilog] (Section~\goto{1.5}[sec:proof:htl_verilog]), and
+finally, the proof that Verilog is deterministic is given in
+Lemma~\goto{{[}lemma:deterministic{]}}[lemma:deterministic]
+(Section~\goto{1.6}[sec:proof:deterministic]).
+
+\subsection[sec:proof:3ac_htl]{Forward Simulation from 3AC to HTL}
+
+As HTL is quite far removed from 3AC, this first translation is the most involved and therefore
+requires a larger proof, because the translation from 3AC instructions to Verilog statements needs
+to be proven correct in this step. In addition to that, the semantics of HTL are also quite
+different to the 3AC semantics. Instead of defining small-step semantics for each construct in
+Verilog, the semantics are defined over one clock cycle and mirror the semantics defined for
+Verilog.  Lemma~\goto{{[}lemma:htl{]}}[lemma:htl] shows the result that needs to be proven in this
+subsection.
+
+\reference[lemma:htl]{} Writing \type{tr_htl} for the translation from 3AC to HTL, we have:
+
+%\startformula \forall c, h, B \in \mono{Safe},\quad \yhfunction{tr\_htl} (c) = \yhconstant{OK} (h) \land c \Downarrow B \implies h \Downarrow B. \stopformula
+
+{\em Proof sketch.} We prove this lemma by first establishing a specification of the translation
+function $\mono{tr\_htl}$ that captures its important properties, and then splitting the proof into
+two parts: one to show that the translation function does indeed meet its specification, and one to
+show that the specification implies the desired simulation result. This strategy is in keeping with
+standard practice.~◻
+
+\subsubsection[sec:proof:3ac_htl:specification]{From Implementation to Specification}
+
+The specification for the translation of 3AC instructions into HTL data-path and control logic can
+be defined by the following predicate:
+
+%\startformula \yhfunction{spec\_instr}\ \mathit{fin}\ \mathit{ret}\ \sigma\ \mathit{stk}\ i\ \mathit{data}\ \mathit{control} \stopformula
+
+Here, the $\mathit{control}$ and $\mathit{data}$ parameters are the statements that the current 3AC
+instruction $i$ should translate to. The other parameters are the special registers defined in
+Section~\goto{{[}sec:verilog:integrating{]}}[sec:verilog:integrating].  An example of a rule
+describing the translation of an arithmetic/logical operation from 3AC is the following:
+
+%\startformula \inferrule[Iop]{\yhfunction{tr\_op}\ \mathit{op}\ \vec{a} = \yhconstant{OK}\ e}{\yhfunction{spec\_instr}\ \mathit{fin}\ \mathit{ret}\ \sigma\ \mathit{stk}\ (\yhconstant{Iop}\ \mathit{op}\ \vec{a}\ d\ n)\ (d\ \yhkeyword{<=}\ e)\ (\sigma\ \yhkeyword{<=}\ n)} \stopformula
+
+Assuming that the translation of the operator $\mathit{op}$ with operands $\vec{a}$ is successful
+and results in expression $e$, the rule describes how the destination register $d$ is updated to $e$
+via a non-blocking assignment in the data path, and how the program counter $\sigma$ is updated to
+point to the next CFG node $n$ via another non-blocking assignment in the control logic.
+
+In the following lemma, $\mono{spec\_htl}$ is the top-level specification predicate, which is built
+using $\mono{spec\_instr}$ at the level of instructions.
+
+\reference[lemma:specification]{} If a 3AC program $c$ is translated correctly to an HTL program
+$h$, then the specification of the translation holds.
+
+%\startformula \forall c, h,\quad \yhfunction{tr\_htl} (c) = \yhconstant{OK}(h) \implies \yhfunction{spec\_htl}\ c\ h. \stopformula
+
+\subsubsection[from-specification-to-simulation]{From Specification to Simulation}
+
+To prove that the specification predicate implies the desired forward simulation, we must first
+define a relation that matches each 3AC state to an equivalent HTL state. This relation also
+captures the assumptions made about the 3AC code that we receive from . These assumptions then have
+to be proven to always hold assuming the HTL code was created by the translation algorithm. Some of
+the assumptions that need to be made about the 3AC and HTL code for a pair of states to match are:
+
+\startitemize
+\item
+  The 3AC register file $R$ needs to be \quote{less defined} than the HTL register map $\Gamma_{r}$
+  (written $R \le \Gamma_{r}$). This means that all entries should be equal to each other, unless a
+  value in $R$ is undefined, in which case any value can match it.
+\item
+  The RAM values represented by each Verilog array in $\Gamma_{a}$ need to match the 3AC function's
+  stack contents, which are part of the memory $M$; that is: $M \le \Gamma_{a}$.
+\item
+  The state is well formed, which means that the value of the state register matches the current
+  value of the program counter; that is: $\mathit{pc} = \Gamma_{r}[\sigma]$.
+\stopitemize
+
+We also define the following set $\mathcal{I}$ of invariants that must hold for the current state to
+be valid:
+
+\startitemize
+\item
+  that all pointers in the program use the stack as a base pointer,
+\item
+  that any loads or stores to locations outside of the bounds of the stack result in undefined
+  behaviour (and hence we do not need to handle them),
+\item
+  that $\mathit{rst}$ and $\mathit{fin}$ are not modified and therefore stay at a constant 0
+  throughout execution, and
+\item
+  that the stack frames match.
+\stopitemize
+
+We can now define the simulation diagram for the translation. The 3AC state can be represented by
+the tuple $(R,M,\mathit{pc})$, which captures the register file, memory, and program counter. The
+HTL state can be represented by the pair $(\Gamma_{r}, \Gamma_{a})$, which captures the states of
+all the registers and arrays in the module.  Finally, $\mathcal{I}$ stands for the other invariants
+that need to hold for the states to match.
+
+\reference[lemma:simulation_diagram]{} Given the 3AC state $(R,M,\mathit{pc})$ and the matching HTL
+state $(\Gamma_{r}, \Gamma_{a})$, assuming one step in the 3AC semantics produces state
+$(R',M',\mathit{pc}')$, there exist one or more steps in the HTL semantics that result in matching
+states $(\Gamma_{r}', \Gamma_{a}')$. This is all under the assumption that the specification
+$\mono{spec\_{htl}}$ holds for the translation.
+
+{\em Proof sketch.} This simulation diagram is proven by induction over the operational semantics of
+3AC, which allows us to find one or more steps in the HTL semantics that will produce the same final
+matching state.~◻
+
+\subsection[sec:proof:ram_insertion]{Forward Simulation of RAM Insertion}
+
+%\startformula \begin{gathered}
+%      \inferrule[Idle]{\Gamma_{\rm r}[\mathit{r.en}] = \Gamma_{\rm r}[\mathit{r.u_{en}}]}{((\Gamma_{\rm r}, \Gamma_{\rm a}), \Delta, r) \downarrow_{\text{ram}} \Delta}\\
+%%
+%      \inferrule[Load]{\Gamma_{\rm r}[\mathit{r.en}] \ne \Gamma_{\rm r}[\mathit{r.u_{en}}] \\ \Gamma_{\rm r}[\mathit{r.wr_{en}}] = 0}{((\Gamma_{\rm r}, \Gamma_{\rm a}), (\Delta_{\rm r}, \Delta_{\rm a}), r) \downarrow_{\text{ram}} (\Delta_{\rm r}[\mathit{r.en} \mapsto \mathit{r.u_{en}}, \mathit{r.d_{out}} \mapsto (\Gamma_{\rm a}[\mathit{r.mem}])[ \mathit{r.addr}]], \Delta_{\rm a}) }\\
+%%
+%      \inferrule[Store]{\Gamma_{\rm r}[\mathit{r.en}] \ne \Gamma_{\rm r}[\mathit{r.u_{en}}] \\ \Gamma_{\rm r}[\mathit{r.wr_{en}}] = 1}{((\Gamma_{\rm r}, \Gamma_{\rm a}), (\Delta_{\rm r}, \Delta_{\rm a}), r) \downarrow_{\text{ram}} (\Delta_{\rm r}[\mathit{r.en} \mapsto \mathit{r.u\_en}], \Delta_{\rm a}[\mathit{r.mem} \mapsto (\Gamma_{\rm a}[ \mathit{r.mem}])[\mathit{r.addr} \mapsto \mathit{r.d_{in}}]]) }
+%    \end{gathered} \stopformula
+
+HTL can only represent a single state machine, so we must model the RAM abstractly to reason about
+the correctness of replacing the direct read and writes to the array by loads and stores to a
+RAM. The specification for the RAM is shown in Fig.~\goto{{[}fig:htl_ram_spec{]}}[fig:htl_ram_spec],
+which defines how the RAM $r$ will behave for all the possible combinations of the input signals.
+
+\subsubsection[from-implementation-to-specification]{From Implementation to Specification}
+
+The first step in proving the simulation correct is to build a specification of the translation
+algorithm. There are three possibilities for the transformation of an instruction. For each Verilog
+statement in the map at location $i$, the statement is either a load, a store, or neither. The load
+or store is translated to the equivalent representation using the RAM specification and all other
+instructions are left intact. An example of the specification for the translation of the store
+instruction is shown below, where $\sigma$ is state register, $r$ is the RAM, $d$ and $c$ are the
+input data-path and control logic maps, and $i$ is the current state. ($n$ is the newly inserted
+state, which only applies to the translation of loads.)
+
+%\startformula \begin{gathered}
+%  \inferrule[Store Spec]{ d[i] = (r.mem\mono{[}e_{1}\mono{]} \mono{ <= } e_{2}) \\ t = (r.u\_en \mono{ <= } \neg r.u\_en; r.wr\_en \mono{ <= } 1; r.d\_in \mono{ <= } e_{2}; r.addr \mono{ <= } e_{1})}%
+%  {\yhfunction{spec\_ram\_tr}\ \sigma\ r\ d\ c\ d[i \mapsto t]\ c\ i\ n}\end{gathered} \stopformula
+
+A similar specification is created for the load. We then also prove that the implementation of the
+translation proves that the specification holds.
+
+\subsubsection[from-specification-to-simulation-1]{From Specification to Simulation}
+
+Another simulation proof is performed to prove that the insertion of the RAM is semantics
+preserving. As in Lemma~\goto{{[}lemma:simulation_diagram{]}}[lemma:simulation_diagram], we require
+some invariants that always hold at the start and end of the simulation. The invariants needed for
+the simulation of the RAM insertion are quite different to the previous ones, so we can define these
+invariants $\mathcal{I}_{r}$ to be the following:
+
+\startitemize
+\item
+  The association map for arrays $\Gamma_{a}$ always needs to have the same arrays present, and
+  these arrays should never change in size.
+\item
+  The RAM should always be disabled at the start and the end of each simulation step. (This is why
+  self-disabling RAM is needed.)
+\stopitemize
+
+The other invariants and assumptions for defining two matching states in HTL are quite similar to
+the simulation performed in Lemma~\goto{{[}lemma:simulation_diagram{]}}[lemma:simulation_diagram],
+such as ensuring that the states have the same value, and that the values in the registers are less
+defined. In particular, the less defined relation matches up all the registers, except for the new
+registers introduced by the RAM.
+
+\reference[lemma:htl_ram]{} Given an HTL program, the forward-simulation relation should hold after
+inserting the RAM and wiring the load, store, and control signals.
+
+%\startformula \begin{aligned}
+%    \forall h, h', B \in \mono{Safe},\quad \yhfunction{tr\_ram\_ins}(h) = h' \land h \Downarrow B \implies h' \Downarrow B.
+%  \end{aligned} \stopformula
+
+\subsection[sec:proof:htl_verilog]{Forward Simulation from HTL to Verilog}
+
+The HTL-to-Verilog simulation is conceptually simple, as the only transformation is from the map
+representation of the code to the case-statement representation. The proof is more involved, as the
+semantics of a map structure is quite different to that of the case-statement to which it is
+converted.
+
+\reference[lemma:verilog]{} In the following, we write $\mono{tr\_verilog}$ for the translation from
+HTL to Verilog.  (Note that this translation cannot fail, so we do not need the constructor here.)
+
+%\startformula \begin{aligned}
+    %\forall h, V, B \in \mono{Safe},\quad \yhfunction{tr\_verilog} (h) = V \land h \Downarrow B \implies V \Downarrow B.
+  %\end{aligned} \stopformula
+
+{\em Proof sketch.} The translation from maps to case-statements is done by turning each node of the
+tree into a case-expression containing the same statements. The main difficulty is that a
+random-access structure is being transformed into an inductive structure where a certain number of
+constructors need to be called to get to the correct case.~◻
+
+\subsection[sec:proof:deterministic]{Deterministic Verilog Semantics}
+
+The final lemma we need is that the Verilog semantics is deterministic.  This result allows us to
+replace the forwards simulation we have proved with the backwards simulation we desire.
+
+\reference[lemma:deterministic]{} If a Verilog program $V$ admits behaviours $B_1$ and $B_2$, then
+$B_1$ and $B_2$ must be the same.
+
+%\startformula \forall V, B_{1}, B_{2},\quad V \Downarrow B_{1} \land V \Downarrow B_{2} \implies B_{1} = B_{2}. \stopformula
+
+{\em Proof sketch.} The Verilog semantics is deterministic because the
+order of operation of all the constructs is defined, so there is only
+one way to evaluate the module, and hence only one possible behaviour.
+This was proven for the small-step semantics shown in
+Fig.~\goto{{[}fig:inference_module{]}}[fig:inference_module].~◻
+
+\subsection[coq-mechanisation]{Coq Mechanisation}
+
+lrrrrr & {\bf Coq code} & & {\bf Spec} & & {\bf Total}\crlf
+Data structures and libraries & 280 & --- & --- & 500 & 780\crlf
+Integers and values & 98 & --- & 15 & 968 & 1081\crlf
+HTL semantics & 50 & --- & 181 & 65 & 296\crlf
+HTL generation & 590 & --- & 66 & 3069 & 3725\crlf
+RAM generation & 253 & --- & --- & 2793 & 3046\crlf
+Verilog semantics & 78 & --- & 431 & 235 & 744\crlf
+Verilog generation & 104 & --- & --- & 486 & 590\crlf
+Top-level driver, pretty printers & 318 & 775 & --- & 189 & 1282\crlf
+{\bf Total} & 1721 & 775 & 693 & 8355 & 11544\crlf
+
+The lines of code for the implementation and proof of can be found in
+Table~\goto{{[}tab:proof_statistics{]}}[tab:proof_statistics]. Overall, it took about 1.5
+person-years to build -- about three person-months on implementation and 15 person-months on
+proofs. The largest proof is the correctness proof for the HTL generation, which required
+equivalence proofs between all integer operations supported by and those supported in hardware. From
+the 3069 lines of proof code in the HTL generation, 1189 are for the correctness proof of just the
+load and store instructions. These were tedious to prove correct because of the substantial
+difference between the memory models used, and the need to prove properties such as stores outside
+of the allocated memory being undefined, so that a finite array could be used. In addition to that,
+since pointers in HTL and Verilog are represented as integers, instead of as a separate
+\quote{pointer} type like in the semantics, it was painful to reason about them. Many new theorems
+had to be proven about them in to prove the conversion from pointer to integer. Moreover, the
+second-largest proof of the correct RAM generation includes many proofs about the extensional
+equality of array operations, such as merging arrays with different assignments. As the negative
+edge implies that two merges take place every clock cycle, the proofs about the equality of the
+contents in memory and in the merged arrays become more tedious too.
+
+Looking at the trusted computing base of , the Verilog semantics is 431 lines of code. This and the
+Clight semantics from are the only parts of the compiler that need to be trusted. The Verilog
+semantics specification is therefore much smaller compared to the 1721 lines of the implementation
+that are written in Coq, which are the verified parts of the HLS tool, even when the Clight
+semantics are added. In addition to that, understanding the semantics specification is simpler than
+trying to understand the translation algorithm. We conclude that the trusted base has been
+successfully reduced.
+
+\stopcomponent
diff --git a/chapters/introduction.tex b/chapters/introduction.tex
new file mode 100644
index 0000000..623b56a
--- /dev/null
+++ b/chapters/introduction.tex
@@ -0,0 +1,5 @@
+\startcomponent introduction
+
+\chapter{Introduction}
+
+\stopcomponent
diff --git a/chapters/pipelining.tex b/chapters/pipelining.tex
new file mode 100644
index 0000000..4308188
--- /dev/null
+++ b/chapters/pipelining.tex
@@ -0,0 +1 @@
+\chapter{\ymhfw{} Loop Pipelining}
diff --git a/chapters/schedule.tex b/chapters/schedule.tex
new file mode 100644
index 0000000..9dc8d38
--- /dev/null
+++ b/chapters/schedule.tex
@@ -0,0 +1 @@
+\chapter{Schedule}
diff --git a/chapters/scheduling.tex b/chapters/scheduling.tex
new file mode 100644
index 0000000..5edad2e
--- /dev/null
+++ b/chapters/scheduling.tex
@@ -0,0 +1,587 @@
+\startcomponent scheduling
+\project main
+
+\chapter{Static Scheduling}
+
+\section[introduction]{Introduction}
+
+The use of multicore processors has been increasing drastically, thereby
+making parallelising compilers ever more important. In addition to that,
+the need for custom hardware accelerators is also increasing, as
+traditional processors are not always the best choice for all
+applications. Compilers that support optimisations which can
+automatically parallelise it's input programs are therefore also
+becoming more important, as these back ends all benefit from it. For
+processors, one wants to optimise the pipeline usage as much as
+possible, whereas in hardware one can create custom pipelines, as well
+as making more use out of the spacial properties that hardware offers,
+making instruction parallelism important as well as speculative
+execution. However, with more powerful optimisations there is a greater
+chance to make mistakes in the compiler, making it possible to generate
+programs that behave differently to the input program. An important step
+towards making compilers more reliable is to formally verify these
+optimisations so that it can be guaranteed that bugs are not introduced.
+
+A popular optimisation for processors increasing the instruction
+parallelism of the resulting program is to use scheduling. This is an
+optimisation that is especially important for processors that have deep
+instruction pipelines or multiple functional units that can be used to
+execute instructions in parallel. However, this optimisation is also
+critical for high-level synthesis tools, which generate application
+specific hardware designs based on a software input. Simple scheduling
+algorithms often work on basic blocks, which are sequential lists of
+instructions without any branches. However, this limits what kind of
+reordering the scheduling algorithm can perform. It can never move
+instructions past a branching instruction, even when this might
+drastically improve the performance. Trace scheduling~ is an alternative
+that addresses this issue, by creating paths that might cross branching
+instructions, and scheduling the instructions in that path. However, the
+main problem with trace scheduling is that it is often infeasible on
+large programs, and because of the large design space, it's sometimes
+hard to find an optimal schedule. Superblock~ and hyperblock~ scheduling
+are two subsets of trace scheduling, which compromise on the flexibility
+of trace scheduling to instead build more tractable algorithms.
+Superblock scheduling produces more efficient code for processors with a
+low issue rate, whereas hyperblock scheduling produces more performant
+code for processors with a high issue rate~.
+
+CompCert~ is a compiler that is formally verified in Coq. In addition to
+that, have also added a formally verified hardware back end to CompCert,
+allowing it to also generate provably correct hardware designs. A
+hardware back end is an ideal target for hyperblock scheduling, as the
+issue rate is practically infinite. This paper describes the
+implementation of a hyperblock instruction scheduler in CompCert so that
+it can benefit existing CompCert back ends, as well as support more
+general targets such as scheduling instructions for custom hardware.
+
+\subsection[key-points]{Key Points}
+
+The goal of this paper is to introduce hyperblock scheduling into
+CompCert to allow for advanced and flexible scheduling operations that
+could be beneficial to various different back ends. To this end, the key
+points of this paper are the following:
+
+\startitemize
+\item
+  Description of how hyperblocks are introduced for improved scheduling
+  of instructions, and how these can be built and translated back to
+  instructions without predicates.
+\item
+  Description of the implementation and correctness proof of a system of
+  difference constraints (SDC) scheduling algorithm, which can be
+  adapted to various different scheduling strategies. {\bf {[}{[}JW:}
+  What's the link between hyperblocks and SDC-based scheduling? Are
+  these orthogonal?{\bf {]}{]}}{\bf {[}{[}YH:} Well the original SDC
+  papers only talk about basic blocks, and not SDC hyperblock
+  scheduling. But it's easy enough to adapt. SDC just requires some kind
+  of blocks without control-flow.{\bf {]}{]}} {\bf {[}{[}JW:} Ok cool,
+  so you can have SDC scheduling without hyperblocks. Can you have
+  hyperblocks without SDC scheduling? (I guess so, but just wanted to be
+  completely sure.){\bf {]}{]}}{\bf {[}{[}YH:} Yes exactly, you can
+  perform any type of basic block scheduling on hyperblocks as well I
+  think, as long as you mark the dependencies correctly. But in the
+  worst case you could even just see hyperblocks as basic blocks and
+  ignore predicates. It would still be correct but just less
+  efficient.{\bf {]}{]}}
+
+  {\bf {[}{[}JW:} It would be interesting to make the case for SDC-based
+  scheduling. Is it superior to other scheduling mechanisms? Is it so
+  much superior that it's worth the additional complexity, compared to,
+  say, list scheduling? {\bf {]}{]}}{\bf {[}{[}YH:} SDC scheduling is
+  more flexible with the type of constraint to optimise for (latency /
+  throughput). I don't think it's too meaningful for compilers, where
+  there isn't as much flexibility.{\bf {]}{]}} {\bf {[}{[}JW:} Thanks.
+  Does Vericert have any idea that the scheduling is being performed
+  using SDC? Or is the SDC stuff entirely internal to your unverified
+  OCaml code? That is, could you swap your scheduler with a different
+  one that isn't based on SDC, and not have to change anything in
+  Vericert?{\bf {]}{]}}{\bf {[}{[}YH:} The verified part doesn't know
+  about SDC at all, so it could be changed to any other scheduler that
+  acts on hyperblocks.{\bf {]}{]}}
+\stopitemize
+
+\section[sec:scheduling]{Implementation of Hyperblocks in CompCert}
+
+This section describes the structure of hyperblocks in
+Section~\goto{2.1}[scheduling:hyperblocks]. Then, the structure of two
+extra intermediate languages that were added to CompCert to implement
+hyperblocks are also shown in Section~\goto{2.2}[sec:rtlblockdef].
+
+\subsection[scheduling:hyperblocks]{Hyperblocks as a Generalisation of Basic Blocks}
+
+Basic blocks are popular in intermediate languages because they describe
+a list of sequential instructions that are not separated by
+control-flow. This information can be used by various analysis passes to
+perform optimisations, as these sequences of instructions can be
+reordered in any way as long as their data dependencies are met. One
+such optimisation is scheduling, which reorders instructions to
+eliminate of any delay slots caused by the CPU pipeline.
+
+However, due to control-flow not being allowed in basic blocks, the
+number of instructions that can be scheduled at any one time is limited.
+The boundaries to other basic blocks act as hard boundary to the
+scheduling algorithm. hyperblocks~ allow instructions to be predicated,
+thereby introducing some control-flow information into the blocks, which
+can also be taken into account by the scheduler. For example, any data
+dependency between instructions that have mutually exclusive predicates
+can be removed, as these instructions will never be activate at the same
+time.
+
+\subsection[sec:rtlblockdef]{RTLBlock and RTLPar Intermediate Language Definition}
+
+Figure~\goto{{[}fig:compcert_interm{]}}[fig:compcert_interm] shows the
+intermediate languages introduced to implement hyperblocks in CompCert.
+This consists of new RTLBlock and RTLPar intermediate languages, which
+implement the sequential and parallel semantics of basic blocks
+respectively. The semantics of RTLBlock and RTLPar are based on the
+CompCert RTL intermediate language. However, instead of mapping from
+states to instructions, RTLBlock maps from states to hyperblocks, and
+RTLPar maps from states to parallel hyperblocks, which will be described
+in the next sections.
+
+%\startformula \begin{aligned}
+%    i\ ::=&\ \ \mono{RBnop} \\
+%          &|\  \mono{RBop}\ p?\ \mathit{op}\ \vec{r}\ d \\
+%          &|\  \mono{RBload}\ p?\ \mathit{chunk}\ \mathit{addr}\ \vec{r}\ d \\
+%          &|\  \mono{RBstore}\ p?\ \mathit{chunk}\ \mathit{addr}\ \vec{r}\ s \\
+%          &|\  \mono{RBsetpred}\ p?\ c\ \vec{r}\ d \\
+%  \end{aligned} \stopformula
+%
+%\startformula \begin{aligned}
+%    i_{\mathit{cf}}\ ::=&\ \ \mono{RBcall}\ \mathit{sig}\ f\ \vec{r}\ d\ n \\
+%                        &|\  \mono{RBtailcall}\ \mathit{sig}\ f\ \vec{r} \\
+%                        &|\  \mono{RBbuiltin}\ f_{\mathit{ext}}\ \vec{r}\ r\ n \\
+%                        &|\  \mono{RBcond}\ c\ \vec{r}\ n_{1}\ n_{2} \\
+%                        &|\  \mono{RBjumptable}\ r\ \vec{n} \\
+%                        &|\  \mono{RBreturn}\ r? \\
+%                        &|\  \mono{RBgoto}\ n \\
+%                        &|\  \mono{RBpred\_{cf}}\ P\ i_{\mathit{cf}_{1}}\ i_{\mathit{cf}_{2}} \\
+%  \end{aligned} \stopformula
+
+RTLBlock instructions are split into two types of instructions, standard
+instructions and control-flow instructions. The standard instructions
+are the instructions that can be placed into hyperblocks, whereas
+control-flow instructions are the instructions that can end hyperblocks.
+The standard instructions are shown in
+Figure~\goto{{[}fig:standard_instruction{]}}[fig:standard_instruction],
+whereas the control-flow instructions are shown in
+Figure~\goto{{[}fig:control_flow_instruction{]}}[fig:control_flow_instruction].
+Most instructions are quite similar to their RTL counterparts, however,
+there are some instructions that have been added. \type{RBsetpred} is a
+standard instruction which sets a predicate equal to an evaluated
+condition. This instruction is used during if-conversion to set the
+predicate to the value of the condition in the conditional statement
+instruction. To support proper predicated instructions, each instruction
+therefore also contains an optional predicate which has been set
+beforehand, which produces the hyperblock. In additon to that, there is
+also an extra control-flow instruction called \type{RBpred_cf}, which
+can branch on a predicate an nests more control-flow instructions inside
+of it. This is also necessary for if-conversion, when converting an
+already converted conditional statement, as depending on the predicate,
+a different control-flow instruction may be necessary. {\bf {[}{[}JW:} I
+think there'd be a lot of value in having a picture showing op-chaining
+in action. See tex source for the kind of thing I mean. Probably best
+done as a running example throughout the paper. {\bf {]}{]}}
+
+These instructions are use in RTLBlock as well as in RTLPar. The main
+difference between these two languages is how these instructions are
+arranged within the hyperblock and the execution semantics of the
+hyperblock in the languages. Let $\mathit{hb}_{b}$ be the definition of
+a hyperblock for RTLBlock, and let $\mathit{hb}_{p}$ be the definition
+of a hyperblock for RTLPar, then $\mathit{hb}_{b}$ and $\mathit{hb}_{p}$
+be defined as in Figure~\goto{{[}fig:hb_def{]}}[fig:hb_def]. The Figure
+shows the different nesting levels of the basic blocks in RTLBlock as
+well as RTLPar, and where the parallel semantics of RTLPar come into
+play. RTLBlock is made of a list of instructions and a control-flow
+instruction that ends the hyperblock. Each instruction in RTLBlock is
+executed sequentially. RTLPar is made of three separate lists. The outer
+list behaves like the list in RTLBlock, and executes each list inside of
+it sequentially. RTLPar then has a list which executes it's contents in
+parallel, meaning each instruction uses the same state of the registers
+and memory while executing. Finally, instead of directly containing
+instructions, there is an additional layer of sequentially executing
+lists of instructions, to be able to execute small groups of
+instructions in sequence, but still in parallel to the other
+instructions in the current parallel group.
+
+RTLPar is structured in this way so that the scheduler has more
+flexibility, so that it can not only parallelise operations in the basic
+blocks, but that it can also define sequential operations in these
+parallel operations. This is especially useful for the hardware back
+end, as it means that sequential operations that do not quite fill one
+clock cycle can be executed sequentially, but can still be executed in
+parallel with other independent operations. This optimisation is called
+operation chaining, and is critical to get the most performance out of
+the hardware.
+
+\subsection[translating-rtlblock-to-rtlpar]{Translating RTLBlock to RTLPar}
+
+The translation from RTLBlock to RTLPar is performed using a scheduling
+algorithm, which will takes hyperblocks and rearranges their
+instructions to maximise parallelism based on the data dependencies. It
+then arranges the instructions in RTLPar by putting independent
+instructions into the same parallel block. Scheduling is an optimisation
+that is well suited to translation validation, as the algorithm itself
+can be quite complex, whereas the output is normally relatively easy to
+check for equivalence with the input.
+Figure~\goto{{[}fig:compcert_interm{]}}[fig:compcert_interm] shows that
+the scheduling step comes right after the if-conversion step which
+originally creates the hyperblocks.
+
+Figure~\goto{{[}fig:op_chain{]}}[fig:op_chain] shows how the scheduling
+step transforms RTLBlock into RTLPar. The RTLBlock hyperblock being
+scheduled is shown in
+Figure~\goto{{[}fig:op_chain_a{]}}[fig:op_chain_a], which contains five
+predicated operations, comprising two additions and three
+multiplications. The data dependencies of the instructions in the
+hyperblock are shown in
+Figure~\goto{{[}fig:op_chain_b{]}}[fig:op_chain_b]. Curiously, even
+though operations and are normally dependent on each other due to a
+write-after-write conflict, but because the predicates are independent
+the write-after-write conflict can effectively be removed by the
+scheduler.
+
+The scheduler transforms the RTLBlock hyperblock into the RTLPar
+hyperblock shown in Figure~\goto{{[}fig:op_chain_c{]}}[fig:op_chain_c].
+Even though the addition in is dependent on , they can still be put into
+the same cycle as the additions do not take as long to complete as the
+multiplications. This optimisation is called operation chaining. Then,
+the multiplication in can also be placed in the same clock cycle as it
+does not have any data dependencies. Then, in the next clock cycle,
+either the multiplication in can take place, or the multiplication in
+will take place, meaning these two multiplications can also be placed in
+the same clock cycle. This gives the final schedule that is shown in
+Figure~\goto{{[}fig:op_chain_d{]}}[fig:op_chain_d].
+
+\section[abstr_interp]{Abstract Interpretation of Hyperblocks}
+
+The correctness of the scheduling algorithm is checked by comparing the
+symbolic expressions of each register before and after scheduling. This
+section describes how these symbolic expressions are constructed for
+each hyperblock.
+
+\subsection[abstr_language]{Construction of Abstract Language}
+
+The main difficulty when constructing symbolic expressions for
+hyperblocks is the presence of predicates, which can be used by the
+scheduling algorithm to reorder instructions further, even if these
+contain data dependencies. The scheduling algorithm will manipulate
+predicates in the following ways, which the comparison function needs to
+take into account.
+
+\startitemize
+\item
+  Instructions with predicates that are equivalent to false can be
+  removed.
+\item
+  Instructions with predicates that are mutually exclusive can be
+  executed in parallel.
+\item
+  Any predicate can be replaced with an equivalent predicate.
+\stopitemize
+
+The symbolic expressions have the following form:
+
+There are three main resources that are present in symbolic expressions:
+registers $r$, which represent the value of the registers in the
+program, predicates $p$, which represent the value of the predicates
+throughout the program, and finally, memory \type{Mem}, representing the
+state of the memory. For each basic instruction in the hyperblock, there
+is an equivalent symbolic expression which either modifies the state of
+the registers, predicates or memory. Finally, as each instruction in the
+hyperblock can be predicates, each symbolic expression is also paired
+with a predicate as well.
+
+Assigning the same resource multiple times with instructions that
+contain different predicates, means that the symbolic expression must
+also express this conditional result based on the predicates. This is
+expressed by assigning lists of predicated symbolic expressions to each
+resource, where each predicate needs to be mutually exclusive from the
+other predicates in the list.
+
+The expressions are then constructed using a function which updates the
+symbolic expressions assigned for each resource. This is done using
+multiple primitives which act on predicated types, which are made up of
+a list of pairs of predicates and the element of that type. The first
+important primitive is multiplication of two predicated types, which is
+implemented as performing a cartesian multiplication between the
+predicated types in the two lists, anding the two predicates and joining
+the two types of each list using a function.
+
+%\startformula \label{eq:1}
+%  P_{1} \otimes_{f} P_{2} \equiv \mono{map } (\lambda ((p_{1}, e_{1}), (p_{2}, e_{2})) . (p_{1} \land p_{2}, f\ e_{1}\ e_{2})) P_{1} \times P_{2} \stopformula
+
+In addition to that, another primitive that is needed is the following
+append operation, which will negate the combination of all predicates in
+the second predicated type, and it to the first predicated type and
+append the first predicated type to the second:
+
+%\startformula \label{eq:2}
+%  \mu(p, P) \equiv \mono{map } (\lambda (p', e') . (p \land p', e'))\ P \stopformula
+
+%\startformula \label{eq:3}
+%  P_{1} \oplus_{p} P_{2} \equiv \mu(\neg p, P_{1}) \mathbin{++} \mu(p, P_{2}) \stopformula
+
+\subsection[title={Example of
+translation},reference={example-of-translation}]
+
+%\startformula \begin{aligned}
+%    \label{eq:4}
+%    &\mono{r1} =
+%      \begin{cases}
+%        \mono{r1}^{0} + \mono{r4}^{0} + \mono{r4}^{0}, \quad &\mono{p1} \\
+%        \mono{r1}^{0}, \quad &\mono{!p1} \\
+%      \end{cases}\\
+%    &\mono{r2} = \mono{r1}^{0} + \mono{r4}^{0}\\
+%    &\mono{r3} =
+%      \begin{cases}
+%        \left( \mono{r1}^{0} \times \mono{r1}^{0} \right) \times \left( \mono{r1}^{0} \times \mono{r1}^{0} \right),\quad &\mono{!p2 \&\& !p1}\\
+%        \mono{r1}^{0} \times \mono{r4}^{0},\quad &\mono{p2 \&\& !p1}\\
+%        \left( \mono{r1}^{0} + \mono{r4}^{0} + \mono{r4}^{0} \right) \times \mono{r4}^{0},\quad &\mono{!p2 \&\& p1}\\
+%        \mono{r3}^{0} \times \mono{r3}^{0},\quad &\mono{p2 \&\& p1}
+%      \end{cases}
+%  \end{aligned} \stopformula
+
+Using the example shown in
+Figure~\goto{{[}fig:op_chain{]}}[fig:op_chain], the RTLBlock hyperblock
+shown in Figure~\goto{{[}fig:op_chain_a{]}}[fig:op_chain_a] is scheduled
+into the hyperblock RTLPar shown in
+Figure~\goto{{[}fig:op_chain_c{]}}[fig:op_chain_c]. The first step is to
+translate the input and output of the scheduler into the Abstr
+intermediate language by calculating the symbolic values that will be
+stored in each of the registers. Symbolically evaluating the RTLBlock
+hyperblock results in the expressions shown in
+Figure~\goto{{[}fig:symbolic_expressions{]}}[fig:symbolic_expressions]
+for registers \type{r1}, \type{r2} and \type{r3}, where the state of the
+register \type{r1} at the start of the hyperblock is denoted as
+$\mono{r1}^{0}$.
+
+This symbolic expression can be generated by sequentially going through
+the list of predicated expressions and applying the update function
+defined in Section~\goto{3.1}[abstr_language]. The resulting predicated
+expressions is guaranteed to have predicates which are mutually
+exclusive, meaning if the predicate evaluates to true, all other
+predicates must evaluate to false.
+
+\subsection[title={Linear (Flat) Predicated
+Expressions},reference={linear-flat-predicated-expressions}]
+
+The update function for predicated expressions is quite a bit more
+complex compared to standard update functions for symbolic execution,
+such as the one used by . The main reason for this is the non-recursive
+nature of the predicated expressions. As the predicates are only
+available at the top-level of the expressions, combining multiple
+expressions means that the conditions and multiple possibilities also
+need to trickle up to the top.
+
+Instead, if the predicated instructions were recursive, one would not
+have to change any predicates when evaluating the argument lists of
+instructions, for example, as these can just stay predicated. The
+evaluation semantics would also be much simpler, because a rule can be
+added for evaluating predicates.
+
+\section[title={Correctness of the Abstract
+Interpretation},reference={sec:correctness}]
+
+The correctness of the scheduling step is dependent on the correctness
+of the equivalence check between the two abstract languages. As the
+abstract languages contain predicates, this comparison check cannot just
+be a syntactic comparison between the two languages, because the
+predicates might be different but logically equivalent. Instead, a mixed
+equivalence check is performed using a verified SAT solver and a
+syntactic equivalence check of the actual symbolic expressions.
+
+\subsection[title={Comparing Symbolic Abstract
+Expressions},reference={comparing-symbolic-abstract-expressions}]
+
+Abstract expressions comprise a predicate and a symbolic expression. The
+translation from RTLBlock and RTLPar to Abstract ensures that each
+register will contain a predicated symbolic expression that describes
+the value that will be assigned to it after evaluating the basic block.
+This means that if an expression always produces the same result as
+another expression, that the register will always contain the same
+value. If the RTLBlock program and RTLPar program translate to two
+Abstract languages where all the register's symbolic expressions match,
+then this means that both programs will always produce the same value.
+
+The main comparison between two symbolic expressions can be done using a
+simple syntactic comparison, because this ensures that each of the
+expressions always evaluate to the same value, and is also general
+enough for the expressions that need to be compared. However, as all
+expressions might be predicated, this simple syntactic comparison cannot
+be performed for the predicates. This is because predicated instructions
+can be executed in many different orders, and the predicates are used to
+calculate dependence information and therefore also determine the order
+of operations.
+
+Instead, comparing predicates can be done by checking logical
+equivalence of the predicates using a formally verified SAT solver. This
+ensures that the predicates will always evaluate to the same value,
+thereby making it a fair comparison.
+
+\subsection[title={Verified Decidable DPLL SAT
+Solver},reference={verified_sat}]
+
+A SAT solver is needed to correctly and reliably compare predicated
+expressions. This makes it possible to then compare many different
+possible schedules, even if they remove expressions completely if these
+are unnecessary. The SAT solver is needed in the verifier, which needs
+to be proven correct in Coq to prove the scheduling translation correct.
+The SAT solver therefore has to be verified, because it could otherwise
+not be used in the proof of correctness.
+
+The DPLL algorithm is used to implement the SAT solver. This means that
+the SAT solver takes in a conjunctive normal form (CNF) formula. The
+conversion from a recursive predicate type into a CNF formula is done by
+recursively expanding the predicate in equivalent CNF formulas.
+
+The SAT solver is implemented in Coq and proven to be sound and
+complete. The soundness and completeness of an algorithm to check
+whether a predicate is satisfiable or not also directly implies that the
+check is decidable, simplifying many proofs in Coq by using a
+\type{Setoid} instance for equivalence between predicates. This makes
+rewriting predicates if they are equivalent much easier in proofs by
+reusing many of the existing Coq tactics.
+
+\subsection[title={Encoding Predicated Expressions as SAT
+Formulas},reference={encoding-predicated-expressions-as-sat-formulas}]
+
+Given the following two predicated expressions which should be tested
+for equivalence, one can construct a SAT expression which will ensure
+that both expressions will always result in the same value.
+
+%\startformula \begin{aligned}
+%  \bgroup \left.\begin{aligned}
+%    e_{1},\qquad &p_{1}\\
+%    e_{2},\qquad &p_{2}\\
+%    \vdots\quad& \\
+%    e_{n},\qquad &p_{n}\\
+%  \end{aligned}\right\rbrace\egroup
+%  \Longleftrightarrow
+%  \begin{cases}
+%    e_{1}',\quad &p_{1}'\\
+%    e_{2}',\quad &p_{2}'\\
+%    \;\;\;\quad\vdots \notag \\
+%    e_{m}',\quad &p_{m}'\\
+%  \end{cases}\end{aligned} \stopformula
+
+The SAT query that should determine if two predicated expressions are
+equivalent is the following, where $\mathit{he}_{i}$ is the hashed
+expression of $e_{i}$:
+
+%\startformula \begin{gathered}
+%  (p_{1} \implies \mathit{he}_{1}) \land (p_{2} \implies \mathit{he}_{2}) \land \cdots \land (p_{n} \implies \mathit{he}_{n}) \\
+%  \Longleftrightarrow\\
+%  (p_{1}' \implies \mathit{he}_{1}') \land (p_{2}' \implies \mathit{he}_{2}') \land \cdots \land (p_{m}' \implies \mathit{he}_{m}') \\\end{gathered} \stopformula
+
+However, reasoning about the equivalence of individual expressions
+within the greater list of predicated expressions is not quite
+straightforward. The evaluation semantics of predicated expression list
+will evaluate each predicate expression sequentially, and pick the
+expression whose predicate evaluates to true. However, proving that both
+predicated expression lists will return the same value assuming that the
+SAT query above is true, means that for each predicate that is true, One
+needs to be able to show that there is a predicate in the other list
+that will also be true, which will return the same value. However, there
+is no guarantee that there is a unique predicated expression that will
+match the current predicate, as there may be duplicate expressions in
+the list with different predicates.
+
+This means that it is quite difficult to prove that the SAT query
+implies the semantic preservation of the scheduling transformation. The
+SAT query can therefore be broken down into a slightly more direct
+comparison that is more useful for the proof itself. The steps to
+perform the more fine grained comparison are the following:
+
+%\startenumerate[n]
+%\item
+%  Hash all of the expressions into a unique literal.
+%\item
+%  Create a map from expression literals to their corresponding
+%  predicate, thereby having a unique predicate for each expressions. If
+%  there are duplicates in the list that forms the map, the predicates
+%  are combined using the or operation.
+%\item
+%  Iterate through the expressions in both maps and compare the
+%  predicates using the SAT solver. If an expression is not present in
+%  one of the maps, then it's predicate should be equivalent to $\perp$.
+%\stopenumerate
+
+This comparison is logically equivalent to performing the large SAT
+query, however, it maps better to the proof because it is comparing the
+predicates of the same expressions with each other.
+
+\subsection[proof-of-equivalence-between-passes]{Proof of equivalence between passes}
+
+Figure~\goto{{[}fig:compcert_interm{]}}[fig:compcert_interm] shows the
+four different passes that were added to CompCert to form hyperblocks.
+This section will cover the proofs for each of the translations,
+focusing mainly on the proof of translation of the scheduling pass.
+
+\subsubsection[proof-of-correctness-of-the-if-conversion-pass]{Proof of Correctness of the
+  If-Conversion Pass}
+
+The if-conversion pass is quite simple to verify, as it is an
+optimisation that transforms the code in the same language.
+
+\subsubsection[proof-of-correctness-of-scheduling]{Proof of Correctness of Scheduling}
+
+The scheduling pass is formally verified using translation validation,
+using the Abstr language as a point of comparison between RTLBlock and
+RTLPar. Using the algorithm defined in Section~\goto{3}[abstr_interp],
+the formally verified SAT solver described in
+Section~\goto{4.2}[verified_sat] can be used prove that if the two
+predicated expression lists are equivalent, that they will always
+evaluate to the same value.
+
+\section[implementation-details-of-static-sdc-scheduling]{Implementation Details of Static SDC
+  Scheduling}
+
+This section describes the implementation details of the static SDC
+scheduling algorithm used, and also describes some of the details of the
+basic block generation as well as the if-conversion pass which generates
+the predicated instructions.
+
+\subsection[implementation-of-if-conversion]{Implementation of If-Conversion}
+
+If-conversion is the conversion that introduces predicated instructions
+which can make use of the hyperblocks. It converts conditional
+statements into predicated instructions. This transformation has a few
+limitations on the kind of conditional statements that it can translate.
+First, only conditional statements without loops can be translated,
+therefore, one must identify cycles in the control-flow before
+performing the if-conversion. Secondly, if-conversion will not always
+result in more efficient code, so it should not be applied to any
+conditional statements. Instead, it is best applied to conditional
+statements where each branch will take a similar amount of time to
+execute.
+
+For back ends that do not support predicates, it is also important to
+eliminate the predicates again using a process called reverse
+if-conversion, which creates branches out of the predicates and groups
+these together again. This allows for hyperblock scheduling to also be
+used with back ends that do not support predicates, which are most the
+default back ends included in CompCert.
+
+\subsection[title={Static SDC
+Scheduling},reference={static-sdc-scheduling}]
+
+System of difference constraints (SDC) scheduling~ is a flexible
+algorithm to perform scheduling of instructions, especially if the
+target is hardware directly. It allows for flexible definitions of
+optimisation functions in terms of latencies and dependencies of the
+operations in the basic block.
+
+\section[title={Performance
+Comparison},reference={performance-comparison}]
+
+\section[title={Related Work},reference={sec:related-work}]
+
+\section[title={Conclusion},reference={conclusion}]
+
+This material is based upon work supported by the under Grant No.~ and
+Grant No.~. Any opinions, findings, and conclusions or recommendations
+expressed in this material are those of the author and do not
+necessarily reflect the views of the National Science Foundation.
+
+\stopcomponent