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+title = "Complex optimisation effects"
+author = "Yann Herklotz"
+tags = []
+categories = []
+backlinks = ["1f3"]
+forwardlinks = ["1f4a"]
+zettelid = "1f4"
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+
+Finally, the last flakiness property that HLS tools have is that they
+apply many optimisations, which may or may not have linear effects on
+the performance and area of the result.
+
+> Because of Amdahl's law arguments, most optimizations don't have a
+> linear effect. They appear to have a linear effect sometimes, but
+> eventually hit some diminishing returns. Some other effects are really
+> discontinuous, for instance, unrolling accumulation loops may not
+> change critical recurrences. — Stephen Neuendorffer ([email])
+
+It's is nearly impossible to predict what a series of optimisations will
+do to the performance. The user will implicitly try to predict the
+performance with a simplified model as reference, and as the HLS tool
+has to take everything into account, and will therefore sometimes not be
+able to optimise the loop as the user would want it to be, leading to
+discontinuous optimisations.
+
+  [email]: notmuch:id:BYAPR02MB3910A2FA9F954031FC11A232A8479@BYAPR02MB3910.namprd02.prod.outlook.com