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<dt>Revision</dt> <dd><a href="http://trac.webkit.org/projects/webkit/changeset/201866">201866</a></dd>
<dt>Author</dt> <dd>cdumez@apple.com</dd>
<dt>Date</dt> <dd>2016-06-09 09:31:38 -0700 (Thu, 09 Jun 2016)</dd>
</dl>
<h3>Log Message</h3>
<pre>Unreviewed, rolling out <a href="http://trac.webkit.org/projects/webkit/changeset/201836">r201836</a>, <a href="http://trac.webkit.org/projects/webkit/changeset/201845">r201845</a>, and <a href="http://trac.webkit.org/projects/webkit/changeset/201848">r201848</a>.
Looks like a 1-2% PLT regression on iOS
Reverted changesets:
"[JSC] Change some parameters based on a random search"
https://bugs.webkit.org/show_bug.cgi?id=158514
http://trac.webkit.org/changeset/201836
"Tempory fix for the debug bots"
http://trac.webkit.org/changeset/201845
"Change thresholdForOptimizeSoon to match
thresholdForOptimizeAfterWarmUp"
http://trac.webkit.org/changeset/201848</pre>
<h3>Modified Paths</h3>
<ul>
<li><a href="#trunkSourceJavaScriptCoreChangeLog">trunk/Source/JavaScriptCore/ChangeLog</a></li>
<li><a href="#trunkSourceJavaScriptCorebytecodeCodeBlockcpp">trunk/Source/JavaScriptCore/bytecode/CodeBlock.cpp</a></li>
<li><a href="#trunkSourceJavaScriptCoreruntimeOptionsh">trunk/Source/JavaScriptCore/runtime/Options.h</a></li>
<li><a href="#trunkToolsChangeLog">trunk/Tools/ChangeLog</a></li>
<li><a href="#trunkToolsScriptsrunjscstresstests">trunk/Tools/Scripts/run-jsc-stress-tests</a></li>
</ul>
</div>
<div id="patch">
<h3>Diff</h3>
<a id="trunkSourceJavaScriptCoreChangeLog"></a>
<div class="modfile"><h4>Modified: trunk/Source/JavaScriptCore/ChangeLog (201865 => 201866)</h4>
<pre class="diff"><span>
<span class="info">--- trunk/Source/JavaScriptCore/ChangeLog 2016-06-09 15:56:07 UTC (rev 201865)
+++ trunk/Source/JavaScriptCore/ChangeLog 2016-06-09 16:31:38 UTC (rev 201866)
</span><span class="lines">@@ -1,3 +1,22 @@
</span><ins>+2016-06-09 Chris Dumez <cdumez@apple.com>
+
+ Unreviewed, rolling out r201836, r201845, and r201848.
+
+ Looks like a 1-2% PLT regression on iOS
+
+ Reverted changesets:
+
+ "[JSC] Change some parameters based on a random search"
+ https://bugs.webkit.org/show_bug.cgi?id=158514
+ http://trac.webkit.org/changeset/201836
+
+ "Tempory fix for the debug bots"
+ http://trac.webkit.org/changeset/201845
+
+ "Change thresholdForOptimizeSoon to match
+ thresholdForOptimizeAfterWarmUp"
+ http://trac.webkit.org/changeset/201848
+
</ins><span class="cx"> 2016-06-09 Commit Queue <commit-queue@webkit.org>
</span><span class="cx">
</span><span class="cx"> Unreviewed, rolling out r201810.
</span></span></pre></div>
<a id="trunkSourceJavaScriptCorebytecodeCodeBlockcpp"></a>
<div class="modfile"><h4>Modified: trunk/Source/JavaScriptCore/bytecode/CodeBlock.cpp (201865 => 201866)</h4>
<pre class="diff"><span>
<span class="info">--- trunk/Source/JavaScriptCore/bytecode/CodeBlock.cpp 2016-06-09 15:56:07 UTC (rev 201865)
+++ trunk/Source/JavaScriptCore/bytecode/CodeBlock.cpp 2016-06-09 16:31:38 UTC (rev 201866)
</span><span class="lines">@@ -3616,17 +3616,68 @@
</span><span class="cx">
</span><span class="cx"> double CodeBlock::optimizationThresholdScalingFactor()
</span><span class="cx"> {
</span><del>- // We want a good threshold based on the instruction count.
- // Here, we are trying to optimize the following formula:
- // F[x_] =: a * Sqrt[x + b] + Abs[c * x] + d
</del><ins>+ // This expression arises from doing a least-squares fit of
</ins><span class="cx"> //
</span><del>- // The parameters were chosen by testing random values
- // between 1 and 2 and keeping the best combination.
- const double a = Options::optimizationThresholdScalingFactorA();
- const double b = Options::optimizationThresholdScalingFactorB();
- const double c = Options::optimizationThresholdScalingFactorC();
- const double d = Options::optimizationThresholdScalingFactorD();
</del><ins>+ // F[x_] =: a * Sqrt[x + b] + Abs[c * x] + d
+ //
+ // against the data points:
+ //
+ // x F[x_]
+ // 10 0.9 (smallest reasonable code block)
+ // 200 1.0 (typical small-ish code block)
+ // 320 1.2 (something I saw in 3d-cube that I wanted to optimize)
+ // 1268 5.0 (something I saw in 3d-cube that I didn't want to optimize)
+ // 4000 5.5 (random large size, used to cause the function to converge to a shallow curve of some sort)
+ // 10000 6.0 (similar to above)
+ //
+ // I achieve the minimization using the following Mathematica code:
+ //
+ // MyFunctionTemplate[x_, a_, b_, c_, d_] := a*Sqrt[x + b] + Abs[c*x] + d
+ //
+ // samples = {{10, 0.9}, {200, 1}, {320, 1.2}, {1268, 5}, {4000, 5.5}, {10000, 6}}
+ //
+ // solution =
+ // Minimize[Plus @@ ((MyFunctionTemplate[#[[1]], a, b, c, d] - #[[2]])^2 & /@ samples),
+ // {a, b, c, d}][[2]]
+ //
+ // And the code below (to initialize a, b, c, d) is generated by:
+ //
+ // Print["const double " <> ToString[#[[1]]] <> " = " <>
+ // If[#[[2]] < 0.00001, "0.0", ToString[#[[2]]]] <> ";"] & /@ solution
+ //
+ // We've long known the following to be true:
+ // - Small code blocks are cheap to optimize and so we should do it sooner rather
+ // than later.
+ // - Large code blocks are expensive to optimize and so we should postpone doing so,
+ // and sometimes have a large enough threshold that we never optimize them.
+ // - The difference in cost is not totally linear because (a) just invoking the
+ // DFG incurs some base cost and (b) for large code blocks there is enough slop
+ // in the correlation between instruction count and the actual compilation cost
+ // that for those large blocks, the instruction count should not have a strong
+ // influence on our threshold.
+ //
+ // I knew the goals but I didn't know how to achieve them; so I picked an interesting
+ // example where the heuristics were right (code block in 3d-cube with instruction
+ // count 320, which got compiled early as it should have been) and one where they were
+ // totally wrong (code block in 3d-cube with instruction count 1268, which was expensive
+ // to compile and didn't run often enough to warrant compilation in my opinion), and
+ // then threw in additional data points that represented my own guess of what our
+ // heuristics should do for some round-numbered examples.
+ //
+ // The expression to which I decided to fit the data arose because I started with an
+ // affine function, and then did two things: put the linear part in an Abs to ensure
+ // that the fit didn't end up choosing a negative value of c (which would result in
+ // the function turning over and going negative for large x) and I threw in a Sqrt
+ // term because Sqrt represents my intution that the function should be more sensitive
+ // to small changes in small values of x, but less sensitive when x gets large.
</ins><span class="cx">
</span><ins>+ // Note that the current fit essentially eliminates the linear portion of the
+ // expression (c == 0.0).
+ const double a = 0.061504;
+ const double b = 1.02406;
+ const double c = 0.0;
+ const double d = 0.825914;
+
</ins><span class="cx"> double instructionCount = this->instructionCount();
</span><span class="cx">
</span><span class="cx"> ASSERT(instructionCount); // Make sure this is called only after we have an instruction stream; otherwise it'll just return the value of d, which makes no sense.
</span></span></pre></div>
<a id="trunkSourceJavaScriptCoreruntimeOptionsh"></a>
<div class="modfile"><h4>Modified: trunk/Source/JavaScriptCore/runtime/Options.h (201865 => 201866)</h4>
<pre class="diff"><span>
<span class="info">--- trunk/Source/JavaScriptCore/runtime/Options.h 2016-06-09 15:56:07 UTC (rev 201865)
+++ trunk/Source/JavaScriptCore/runtime/Options.h 2016-06-09 16:31:38 UTC (rev 201866)
</span><span class="lines">@@ -253,28 +253,23 @@
</span><span class="cx"> \
</span><span class="cx"> v(double, jitPolicyScale, 1.0, Normal, "scale JIT thresholds to this specified ratio between 0.0 (compile ASAP) and 1.0 (compile like normal).") \
</span><span class="cx"> v(bool, forceEagerCompilation, false, Normal, nullptr) \
</span><del>- v(int32, thresholdForJITAfterWarmUp, 373, Normal, nullptr) \
- v(int32, thresholdForJITSoon, 169, Normal, nullptr) \
</del><ins>+ v(int32, thresholdForJITAfterWarmUp, 500, Normal, nullptr) \
+ v(int32, thresholdForJITSoon, 100, Normal, nullptr) \
</ins><span class="cx"> \
</span><del>- v(int32, thresholdForOptimizeAfterWarmUp, 511, Normal, nullptr) \
- v(int32, thresholdForOptimizeAfterLongWarmUp, 885, Normal, nullptr) \
- v(int32, thresholdForOptimizeSoon, 511, Normal, nullptr) \
- v(int32, executionCounterIncrementForLoop, 2, Normal, nullptr) \
- v(int32, executionCounterIncrementForEntry, 28, Normal, nullptr) \
</del><ins>+ v(int32, thresholdForOptimizeAfterWarmUp, 1000, Normal, nullptr) \
+ v(int32, thresholdForOptimizeAfterLongWarmUp, 1000, Normal, nullptr) \
+ v(int32, thresholdForOptimizeSoon, 1000, Normal, nullptr) \
+ v(int32, executionCounterIncrementForLoop, 1, Normal, nullptr) \
+ v(int32, executionCounterIncrementForEntry, 15, Normal, nullptr) \
</ins><span class="cx"> \
</span><del>- v(int32, thresholdForFTLOptimizeAfterWarmUp, 99566, Normal, nullptr) \
- v(int32, thresholdForFTLOptimizeSoon, 1566, Normal, nullptr) \
- v(int32, ftlTierUpCounterIncrementForLoop, 6, Normal, nullptr) \
- v(int32, ftlTierUpCounterIncrementForReturn, 13, Normal, nullptr) \
</del><ins>+ v(int32, thresholdForFTLOptimizeAfterWarmUp, 100000, Normal, nullptr) \
+ v(int32, thresholdForFTLOptimizeSoon, 1000, Normal, nullptr) \
+ v(int32, ftlTierUpCounterIncrementForLoop, 1, Normal, nullptr) \
+ v(int32, ftlTierUpCounterIncrementForReturn, 15, Normal, nullptr) \
</ins><span class="cx"> v(unsigned, ftlOSREntryFailureCountForReoptimization, 15, Normal, nullptr) \
</span><span class="cx"> v(unsigned, ftlOSREntryRetryThreshold, 100, Normal, nullptr) \
</span><span class="cx"> \
</span><del>- v(double, optimizationThresholdScalingFactorA, 0.1785461740514816, Normal, nullptr) \
- v(double, optimizationThresholdScalingFactorB, 1.2691392484494950, Normal, nullptr) \
- v(double, optimizationThresholdScalingFactorC, 0.0003675505121227, Normal, nullptr) \
- v(double, optimizationThresholdScalingFactorD, 1.5838284192987762, Normal, nullptr) \
- \
- v(int32, evalThresholdMultiplier, 8, Normal, nullptr) \
</del><ins>+ v(int32, evalThresholdMultiplier, 10, Normal, nullptr) \
</ins><span class="cx"> v(unsigned, maximumEvalCacheableSourceLength, 256, Normal, nullptr) \
</span><span class="cx"> \
</span><span class="cx"> v(bool, randomizeExecutionCountsBetweenCheckpoints, false, Normal, nullptr) \
</span></span></pre></div>
<a id="trunkToolsChangeLog"></a>
<div class="modfile"><h4>Modified: trunk/Tools/ChangeLog (201865 => 201866)</h4>
<pre class="diff"><span>
<span class="info">--- trunk/Tools/ChangeLog 2016-06-09 15:56:07 UTC (rev 201865)
+++ trunk/Tools/ChangeLog 2016-06-09 16:31:38 UTC (rev 201866)
</span><span class="lines">@@ -1,3 +1,22 @@
</span><ins>+2016-06-09 Chris Dumez <cdumez@apple.com>
+
+ Unreviewed, rolling out r201836, r201845, and r201848.
+
+ Looks like a 1-2% PLT regression on iOS
+
+ Reverted changesets:
+
+ "[JSC] Change some parameters based on a random search"
+ https://bugs.webkit.org/show_bug.cgi?id=158514
+ http://trac.webkit.org/changeset/201836
+
+ "Tempory fix for the debug bots"
+ http://trac.webkit.org/changeset/201845
+
+ "Change thresholdForOptimizeSoon to match
+ thresholdForOptimizeAfterWarmUp"
+ http://trac.webkit.org/changeset/201848
+
</ins><span class="cx"> 2016-06-09 Michael Saboff <msaboff@apple.com>
</span><span class="cx">
</span><span class="cx"> WebKitTestRunner and DumpRenderTree do not handle dangling surrogate characters
</span></span></pre></div>
<a id="trunkToolsScriptsrunjscstresstests"></a>
<div class="modfile"><h4>Modified: trunk/Tools/Scripts/run-jsc-stress-tests (201865 => 201866)</h4>
<pre class="diff"><span>
<span class="info">--- trunk/Tools/Scripts/run-jsc-stress-tests 2016-06-09 15:56:07 UTC (rev 201865)
+++ trunk/Tools/Scripts/run-jsc-stress-tests 2016-06-09 16:31:38 UTC (rev 201866)
</span><span class="lines">@@ -428,7 +428,7 @@
</span><span class="cx">
</span><span class="cx"> BASE_OPTIONS = ["--useFTLJIT=false", "--useFunctionDotArguments=true"]
</span><span class="cx"> EAGER_OPTIONS = ["--thresholdForJITAfterWarmUp=10", "--thresholdForJITSoon=10", "--thresholdForOptimizeAfterWarmUp=20", "--thresholdForOptimizeAfterLongWarmUp=20", "--thresholdForOptimizeSoon=20", "--thresholdForFTLOptimizeAfterWarmUp=20", "--thresholdForFTLOptimizeSoon=20", "--maximumEvalCacheableSourceLength=150000"]
</span><del>-NO_CJIT_OPTIONS = ["--useConcurrentJIT=false", "--thresholdForJITAfterWarmUp=100", "--thresholdForJITSoon=100", "--thresholdForOptimizeAfterWarmUp=1000", "--thresholdForOptimizeAfterLongWarmUp=1000", "--thresholdForOptimizeSoon=1000", "--executionCounterIncrementForLoop=1", "--executionCounterIncrementForEntry=15", "--thresholdForFTLOptimizeAfterWarmUp=100000", "--thresholdForFTLOptimizeSoon=1000", "--ftlTierUpCounterIncrementForLoop=1", "--ftlTierUpCounterIncrementForReturn=15", "--evalThresholdMultiplier=10", "--optimizationThresholdScalingFactorA=0.061504", "--optimizationThresholdScalingFactorB=1.02406", "--optimizationThresholdScalingFactorC=0.0", "--optimizationThresholdScalingFactorD=0.825914"]
</del><ins>+NO_CJIT_OPTIONS = ["--useConcurrentJIT=false", "--thresholdForJITAfterWarmUp=100"]
</ins><span class="cx"> FTL_OPTIONS = ["--useFTLJIT=true"]
</span><span class="cx">
</span><span class="cx"> $runlist = []
</span></span></pre>
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