| commit | 7b4e1073226e07d279d6f28883f8aa4b27ade183 | [log] [tgz] |
|---|---|---|
| author | tomhudson@google.com <tomhudson@google.com@2bbb7eff-a529-9590-31e7-b0007b416f81> | Fri Jun 03 19:16:56 2011 +0000 |
| committer | tomhudson@google.com <tomhudson@google.com@2bbb7eff-a529-9590-31e7-b0007b416f81> | Fri Jun 03 19:16:56 2011 +0000 |
| tree | 54d97119dbbf5468691b6cacaac3aa64385bdb98 | |
| parent | c39f17542b058fa746963252c9b8ac40634a4431 [diff] [blame] |
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Issue <a href="/4571045/" onmouseover="M_showPopUp(this, 'popup-issue');">
4571045</a>:
New matrix benchmarks to evaluate ::setConcat implementation options
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<div><b>Created:</b><br>
16 minutes ago by me
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<div><b>Modified:</b><br>
0 minutes ago
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<a href="/user/reed1" onmouseover="M_showUserInfoPopup(this)">reed1</a>
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<pre>On platforms that use Float (instead of Fixed), SkMatrix stores its internal
values as floats, but setConcat() needs extra precision and so uses doubles to
contain intermediate values.
These three benchmarks compare the speed of float-only, double-only, and
float-cast-to-double implementations of a chunk of code extracted from the
non-perspective case of setConcat().
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13 minutes ago
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1. lets remove the "fix" from the function name. just muladdmul I think 2. we ...
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<pre name="cl-message-1">1. lets remove the "fix" from the function name. just muladdmul I think
2. we can remove the return, since it will be compiled away anyway
3. nice checkin comment!
4. what are the results like?</pre>
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> 4. what are the results like? For posterity: tomhudson@tomhudson-zx600-linux:/usr/local/google/src/skia3$ out/bench/bench -match matrix_concat -repeat 1000 ...
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<pre name="cl-message-2">> 4. what are the results like?
For posterity:
tomhudson@tomhudson-zx600-linux:/usr/local/google/src/skia3$ out/bench/bench
-match matrix_concat -repeat 1000
skia bench: alpha=0xFF antialias=1 filter=0
running bench [640 480] matrix_concat_double 8888: msecs = 0.79 565:
msecs = 0.79 GPU: msecs = 0.79
running bench [640 480] matrix_concat_floatdouble 8888: msecs = 0.97 565:
msecs = 0.97 GPU: msecs = 0.97
running bench [640 480] matrix_concat_float 8888: msecs = 0.74 565:
msecs = 0.73 GPU: msecs = 0.74</pre>
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<b>Issue 4571045: New matrix benchmarks to evaluate ::setConcat implementation options
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Created 16 minutes ago by me<br>
Modified 0 minutes ago<br>
Reviewers: reed1<br>
Base URL: http://skia.googlecode.com/svn/trunk/<br>
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On platforms that use Float (instead of Fixed), SkMatrix stores its internal
values as floats, but setConcat() needs extra precision and so uses doubles
to contain intermediate values.
These three benchmarks compare the speed of float-only, double-only, and
float-cast-to-double implementations of a chunk of code extracted from the
non-perspective case of setConcat().
git-svn-id: http://skia.googlecode.com/svn/trunk@1497 2bbb7eff-a529-9590-31e7-b0007b416f81
diff --git a/bench/MatrixBench.cpp b/bench/MatrixBench.cpp index 1c99ab4..72dfe8b 100644 --- a/bench/MatrixBench.cpp +++ b/bench/MatrixBench.cpp
@@ -1,5 +1,6 @@ #include "SkBenchmark.h" #include "SkMatrix.h" +#include "SkRandom.h" #include "SkString.h" class MatrixBench : public SkBenchmark { @@ -45,7 +46,7 @@ protected: virtual void performTest() { SkMatrix m0, m1, m2; - + m0.reset(); m1.reset(); m2.reset(); @@ -63,7 +64,7 @@ class ScaleMatrixBench : public MatrixBench { public: ScaleMatrixBench(void* param) : INHERITED(param, "scale") { - + fM0.reset(); fM1.setScale(fSX, fSY); fM2.setTranslate(fSX, fSY); @@ -82,9 +83,116 @@ typedef MatrixBench INHERITED; }; +// Test the performance of setConcat() non-perspective case: +// using floating point precision only. +class FloatConcatMatrixBench : public MatrixBench { +public: + FloatConcatMatrixBench(void* param) + : INHERITED(param, "concat_float") { + } +protected: + static inline void muladdmul(float a, float b, float c, float d, + float* result) { + *result = a * b + c * d; + } + virtual void performTest() { + float a[9]; + float b[9]; + float r[9]; + a[0] = rnd.nextS(); + a[3] = rnd.nextS(); + muladdmul(a[0], b[0], a[1], b[3], &r[0]); + muladdmul(a[0], b[1], a[1], b[4], &r[1]); + muladdmul(a[0], b[2], a[1], b[5], &r[2]); + muladdmul(a[3], b[0], a[4], b[3], &r[3]); + muladdmul(a[3], b[1], a[4], b[4], &r[4]); + muladdmul(a[3], b[2], a[4], b[5], &r[5]); + always_do(r[0] + r[1] + r[2] + r[3] + r[4] + r[5] + + r[6] + r[7] + r[8] > 0.0f); + } +private: + SkRandom rnd; + typedef MatrixBench INHERITED; +}; + +static inline float SkDoubleToFloat(double x) { + return static_cast<float>(x); +} + +// Test the performance of setConcat() non-perspective case: +// using floating point precision but casting up to float for +// intermediate results during computations. +class FloatDoubleConcatMatrixBench : public MatrixBench { +public: + FloatDoubleConcatMatrixBench(void* param) + : INHERITED(param, "concat_floatdouble") { + } +protected: + static inline void muladdmul(float a, float b, float c, float d, + float* result) { + *result = SkDoubleToFloat((double)a * b + (double)c * d); + } + virtual void performTest() { + float a[9]; + float b[9]; + float r[9]; + a[0] = rnd.nextS(); + a[3] = rnd.nextS(); + muladdmul(a[0], b[0], a[1], b[3], &r[0]); + muladdmul(a[0], b[1], a[1], b[4], &r[1]); + muladdmul(a[0], b[2], a[1], b[5], &r[2]); + muladdmul(a[3], b[0], a[4], b[3], &r[3]); + muladdmul(a[3], b[1], a[4], b[4], &r[4]); + muladdmul(a[3], b[2], a[4], b[5], &r[5]); + always_do(r[0] + r[1] + r[2] + r[3] + r[4] + r[5] + + r[6] + r[7] + r[8] > 0.0f); + } +private: + SkRandom rnd; + typedef MatrixBench INHERITED; +}; + +// Test the performance of setConcat() non-perspective case: +// using double precision only. +class DoubleConcatMatrixBench : public MatrixBench { +public: + DoubleConcatMatrixBench(void* param) + : INHERITED(param, "concat_double") { + } +protected: + static inline void muladdmul(double a, double b, double c, double d, + double* result) { + *result = a * b + c * d; + } + virtual void performTest() { + double a[9]; + double b[9]; + double r[9]; + a[0] = rnd.nextS(); + a[3] = rnd.nextS(); + muladdmul(a[0], b[0], a[1], b[3], &r[0]); + muladdmul(a[0], b[1], a[1], b[4], &r[1]); + muladdmul(a[0], b[2], a[1], b[5], &r[2]); + muladdmul(a[3], b[0], a[4], b[3], &r[3]); + muladdmul(a[3], b[1], a[4], b[4], &r[4]); + muladdmul(a[3], b[2], a[4], b[5], &r[5]); + always_do(r[0] + r[1] + r[2] + r[3] + r[4] + r[5] + + r[6] + r[7] + r[8] > 0.0f); + } +private: + SkRandom rnd; + typedef MatrixBench INHERITED; +}; + + static SkBenchmark* M0(void* p) { return new EqualsMatrixBench(p); } static SkBenchmark* M1(void* p) { return new ScaleMatrixBench(p); } +static SkBenchmark* M2(void* p) { return new FloatConcatMatrixBench(p); } +static SkBenchmark* M3(void* p) { return new FloatDoubleConcatMatrixBench(p); } +static SkBenchmark* M4(void* p) { return new DoubleConcatMatrixBench(p); } static BenchRegistry gReg0(M0); static BenchRegistry gReg1(M1); - +static BenchRegistry gReg2(M2); +static BenchRegistry gReg3(M3); +static BenchRegistry gReg4(M4);