can you try it with c math functions? instead of std.math, try to use core.stdc.math
On Sat, Apr 7, 2018 at 8:53 PM, Arun Chandrasekaran via Digitalmars-d-learn <digitalmars-d-learn@puremagic.com> wrote: > What am I doing wrong here that makes the D equivalent 2.5 times slower > than it's C equivalent? > > Compilers used: > > LDC2: LDC - the LLVM D compiler (1.8.0) > GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.9) 5.4.0 20160609 > > 11:36:39 ~/code/c/test2$ ldc2 sigmoid.d -O5 && ./sigmoid > Max deviation is 0.001664 > 10^7 iterations using sigmoid1: 308 ms > 10^7 iterations using sigmoid2: 30 ms > 11:36:55 ~/code/c/test2 > $ gcc sigmoid.c -o sigmoid-c -O3 -lm 2>/dev/null && ./sigmoid-c > Max deviation is 0.001664 > 10^7 iterations using sigmoid1: 134 ms > 10^7 iterations using sigmoid2: 29 ms > 11:37:10 ~/code/c/test2 > $ > > C code, taken from https://stackoverflow.com/ques > tions/412019/math-optimization-in-c-sharp#412176: > > ``` > #include <math.h> > #include <stdio.h> > #include <time.h> > > #define SCALE 320.0f > #define RESOLUTION 2047 > #define MIN -RESOLUTION / SCALE > #define MAX RESOLUTION / SCALE > > static float sigmoid_lut[RESOLUTION + 1]; > > void init_sigmoid_lut(void) { > int i; > for (i = 0; i < RESOLUTION + 1; i++) { > sigmoid_lut[i] = (1.0 / (1.0 + exp(-i / SCALE))); > } > } > > static float sigmoid1(const float value) { > return (1.0f / (1.0f + expf(-value))); > } > > static float sigmoid2(const float value) { > if (value <= MIN) return 0.0f; > if (value >= MAX) return 1.0f; > if (value >= 0) return sigmoid_lut[(int)(value * SCALE + 0.5f)]; > return 1.0f-sigmoid_lut[(int)(-value * SCALE + 0.5f)]; > } > > float test_error() { > float x; > float emax = 0.0; > > for (x = -10.0f; x < 10.0f; x+=0.00001f) { > float v0 = sigmoid1(x); > float v1 = sigmoid2(x); > float error = fabsf(v1 - v0); > if (error > emax) { emax = error; } > } > return emax; > } > > int sigmoid1_perf() { > clock_t t0, t1; > int i; > float x, y = 0.0f; > > t0 = clock(); > for (i = 0; i < 10; i++) { > for (x = -5.0f; x <= 5.0f; x+=0.00001f) { > y = sigmoid1(x); > } > } > t1 = clock(); > printf("", y); /* To avoid sigmoidX() calls being optimized away */ > return (t1 - t0) / (CLOCKS_PER_SEC / 1000); > } > > int sigmoid2_perf() { > clock_t t0, t1; > int i; > float x, y = 0.0f; > t0 = clock(); > for (i = 0; i < 10; i++) { > for (x = -5.0f; x <= 5.0f; x+=0.00001f) { > y = sigmoid2(x); > } > } > t1 = clock(); > printf("", y); /* To avoid sigmoidX() calls being optimized away */ > return (t1 - t0) / (CLOCKS_PER_SEC / 1000); > } > > int main(void) { > init_sigmoid_lut(); > printf("Max deviation is %0.6f\n", test_error()); > printf("10^7 iterations using sigmoid1: %d ms\n", sigmoid1_perf()); > printf("10^7 iterations using sigmoid2: %d ms\n", sigmoid2_perf()); > > return 0; > } > ``` > > D equivalent: > > ``` > module sigmoid; > > import std.stdio; > import std.math; > import std.datetime.stopwatch; > > enum SCALE = 320.0f; > enum RESOLUTION = 2047; > enum MIN = -RESOLUTION / SCALE; > enum MAX = RESOLUTION / SCALE; > > float[RESOLUTION + 1] sigmoid_lut; > > void init_sigmoid_lut() { > int i; > for (i = 0; i < RESOLUTION + 1; i++) { > sigmoid_lut[i] = (1.0 / (1.0 + exp(-i / SCALE))); > } > } > > private float sigmoid1(const float value) { > return (1.0f / (1.0f + exp(-value))); > } > > private float sigmoid2(const float value) { > if (value <= MIN) return 0.0f; > if (value >= MAX) return 1.0f; > if (value >= 0) return sigmoid_lut[cast(int)(value * SCALE + 0.5f)]; > return 1.0f-sigmoid_lut[cast(int)(-value * SCALE + 0.5f)]; > } > > private float test_error() { > float x; > float emax = 0.0; > > for (x = -10.0f; x < 10.0f; x+=0.00001f) { > float v0 = sigmoid1(x); > float v1 = sigmoid2(x); > float error = fabs(v1 - v0); > if (error > emax) { emax = error; } > } > return emax; > } > > private auto sigmoid1_perf() { > auto sw = StopWatch(AutoStart.yes); > int i; > float x, y = 0.0f; > > for (i = 0; i < 10; i++) { > for (x = -5.0f; x <= 5.0f; x+=0.00001f) { > y = sigmoid1(x); > } > } > return sw.peek.total!"msecs"; > } > > private auto sigmoid2_perf() { > auto sw = StopWatch(AutoStart.yes); > int i; > float x, y = 0.0f; > for (i = 0; i < 10; i++) { > for (x = -5.0f; x <= 5.0f; x+=0.00001f) { > y = sigmoid2(x); > } > } > return sw.peek.total!"msecs"; > } > > int main() { > init_sigmoid_lut(); > writefln("Max deviation is %0.6f", test_error()); > writefln("10^7 iterations using sigmoid1: %s ms", sigmoid1_perf()); > writefln("10^7 iterations using sigmoid2: %s ms", sigmoid2_perf()); > > return 0; > } > ``` >
