blob: d963bc71262053c43e03bd9f5b86ac570b6b7a90 [file] [log] [blame]
#include "SkBenchmark.h"
#include "SkMatrix.h"
#include "SkRandom.h"
#include "SkString.h"
class MatrixBench : public SkBenchmark {
SkString fName;
enum { N = 100000 };
public:
MatrixBench(void* param, const char name[]) : INHERITED(param) {
fName.printf("matrix_%s", name);
}
virtual void performTest() = 0;
protected:
virtual int mulLoopCount() const { return 1; }
virtual const char* onGetName() {
return fName.c_str();
}
virtual void onDraw(SkCanvas* canvas) {
int n = N * this->mulLoopCount();
for (int i = 0; i < n; i++) {
this->performTest();
}
}
private:
typedef SkBenchmark INHERITED;
};
// we want to stop the compiler from eliminating code that it thinks is a no-op
// so we have a non-static global we increment, hoping that will convince the
// compiler to execute everything
int gMatrixBench_NonStaticGlobal;
#define always_do(pred) \
do { \
if (pred) { \
++gMatrixBench_NonStaticGlobal; \
} \
} while (0)
class EqualsMatrixBench : public MatrixBench {
public:
EqualsMatrixBench(void* param) : INHERITED(param, "equals") {}
protected:
virtual void performTest() {
SkMatrix m0, m1, m2;
m0.reset();
m1.reset();
m2.reset();
always_do(m0 == m1);
always_do(m1 == m2);
always_do(m2 == m0);
always_do(m0.getType());
always_do(m1.getType());
always_do(m2.getType());
}
private:
typedef MatrixBench INHERITED;
};
class ScaleMatrixBench : public MatrixBench {
public:
ScaleMatrixBench(void* param) : INHERITED(param, "scale") {
fM0.reset();
fM1.setScale(fSX, fSY);
fM2.setTranslate(fSX, fSY);
fSX = fSY = SkFloatToScalar(1.5f);
}
protected:
virtual void performTest() {
SkMatrix m;
m = fM0; m.preScale(fSX, fSY);
m = fM1; m.preScale(fSX, fSY);
m = fM2; m.preScale(fSX, fSY);
}
private:
SkMatrix fM0, fM1, fM2;
SkScalar fSX, fSY;
typedef MatrixBench INHERITED;
};
// having unknown values in our arrays can throw off the timing a lot, perhaps
// handling NaN values is a lot slower. Anyway, this guy is just meant to put
// reasonable values in our arrays.
template <typename T> void init9(T array[9]) {
SkRandom rand;
for (int i = 0; i < 9; i++) {
array[i] = rand.nextSScalar1();
}
}
// Test the performance of setConcat() non-perspective case:
// using floating point precision only.
class FloatConcatMatrixBench : public MatrixBench {
public:
FloatConcatMatrixBench(void* p) : INHERITED(p, "concat_floatfloat") {
init9(mya);
init9(myb);
init9(myr);
}
protected:
virtual int mulLoopCount() const { return 4; }
static inline void muladdmul(float a, float b, float c, float d,
float* result) {
*result = a * b + c * d;
}
virtual void performTest() {
const float* a = mya;
const float* b = myb;
float* r = myr;
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]);
r[2] += a[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]);
r[5] += a[5];
r[6] = r[7] = 0.0f;
r[8] = 1.0f;
}
private:
float mya [9];
float myb [9];
float myr [9];
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* p) : INHERITED(p, "concat_floatdouble") {
init9(mya);
init9(myb);
init9(myr);
}
protected:
virtual int mulLoopCount() const { return 4; }
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() {
const float* a = mya;
const float* b = myb;
float* r = myr;
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]);
r[2] += a[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]);
r[5] += a[5];
r[6] = r[7] = 0.0f;
r[8] = 1.0f;
}
private:
float mya [9];
float myb [9];
float myr [9];
typedef MatrixBench INHERITED;
};
// Test the performance of setConcat() non-perspective case:
// using double precision only.
class DoubleConcatMatrixBench : public MatrixBench {
public:
DoubleConcatMatrixBench(void* p) : INHERITED(p, "concat_double") {
init9(mya);
init9(myb);
init9(myr);
}
protected:
virtual int mulLoopCount() const { return 4; }
static inline void muladdmul(double a, double b, double c, double d,
double* result) {
*result = a * b + c * d;
}
virtual void performTest() {
const double* a = mya;
const double* b = myb;
double* r = myr;
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]);
r[2] += a[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]);
r[5] += a[5];
r[6] = r[7] = 0.0;
r[8] = 1.0;
}
private:
double mya [9];
double myb [9];
double myr [9];
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);