Here is a link to and entry in bugzilla with attached code. I could not send to the list:
http://bugzilla.xamarin.com/show_bug.cgi?id=2098 On Nov 20, 2011, at 7:41 AM, Jonathan Shore wrote: > Did the code I attached get filtered? I'll post the tar.gz into bugzilla and > send the link. > > Below are code snippets to calculate Ordinary Least Squares, a simpler > example. I found this to be 4x slower than C++ / Java: > > Here is the "safe" and "unsafe" versions of OLS which I ran on an array size > of 50,000 10,000 x: > > public class SafeOLS > { > public static double OLS (double[] x, double[] y) > { > var eXY = 0.0; > var eXX = 0.0; > var eX = 0.0; > var eY = 0.0; > > var len = x.Length; > > for (int i = 0 ; i < len ; i++) > { > var vx = x[i]; > var vy = y[i]; > > eXY += vx*vy; > eXX += vx*vx; > eX += vx; > eY += vy; > } > > var n = (double)len; > return (eXY - eX * eY / n) / (eXX - eX * eX / n); > } > } > > > public class UnSafeOLS > { > unsafe public static double OLS (double[] x, double[] y) > { > var eXY = 0.0; > var eXX = 0.0; > var eX = 0.0; > var eY = 0.0; > > var len = x.Length; > > fixed (double* px = x) > fixed (double* py = y) > { > double* vpx = px; > double* vpy = py; > > for (int i = 0 ; i < len ; i++) > { > var vx = *vpx++; > var vy = *vpy++; > > eXY += vx*vy; > eXX += vx*vx; > eX += vx; > eY += vy; > } > } > > var n = (double)len; > return (eXY - eX * eY / n) / (eXX - eX * eX / n); > } > } > > > One can use the following as a driver, parameterized with 50000, 10000 or > something like that: > > private static void TestUnSafeOLS (int dim, int iterations) > { > double[] x = new double[dim]; > double[] y = new double[dim]; > > for (int i = 0 ; i < x.Length ; i++) > { > x[i] = i; > y[i] = i*i / 1000.0; > } > > Stopwatch watch = new Stopwatch (); > watch.Start(); > > double sum = 0; > for (int i = 0 ; i < iterations ; i++) > { > sum += UnSafeOLS.OLS (x,y); > x[100] = sum; > } > > watch.Stop(); > Console.WriteLine ("unsafe ols: " + sum + ", elapsed: " + > watch.Elapsed); > } > > > Here is the C++ version of OLS: > > > static double OLS (double* x, double* y, int len) > { > double eXY = 0.0; > double eXX = 0.0; > double eX = 0.0; > double eY = 0.0; > > for (int i = 0 ; i < len ; i++) > { > double vx = x[i]; > double vy = y[i]; > > eXY += vx*vy; > eXX += vx*vx; > eX += vx; > eY += vy; > } > > double n = (double)len; > return (eXY - eX * eY / n) / (eXX - eX * eX / n); > } > > static void TestOLS (int dim, int iterations) > { > double* x = new double[dim]; > double* y = new double[dim]; > > for (int i = 0 ; i < dim ; i++) > { > x[i] = i; > y[i] = i*i / 1000.0; > } > > long Tstart = CurrentTimeMilli(); > > double sum = 0; > for (int i = 0 ; i < iterations ; i++) > { > sum += OLS (x,y, dim); > x[100] = sum; > } > > long Tend = CurrentTimeMilli(); > long Telapsed = (Tend-Tstart); > > printf ("OLS: %lf, elapsed: %02d:%02d:%03d\n", sum, (int)(Telapsed / > 60000), (int)(Telapsed % 60000) / 1000, (int)(Telapsed % 1000)); > } > > int main (int argc, char *argv[]) > { > TestOLS (50000, 100000); > return 0; > } > > > Thanks in advance for any pointers and analysis: > > I will send another post with the link in a bit. > Jonathan > > > On Nov 20, 2011, at 3:28 AM, Stefanos A. wrote: > >> 2011/11/20 Jonathan Shore <jonathan.sh...@gmail.com> >> Slide, not really. If mono SIMD had a more general mapping to the GPU, or >> could operate on very large vectors or matrices, possibly. Linear algebra >> is an easy mapping to that stuff. However, I do more complicated stuff >> around timeseries, so does not really fit into linear alg stuff. >> >> I guess, what I'm really after is to understand why the unsafe >> implementation is hardly faster than the "safe" version. Whereas on the >> .NET CLR is 2x as fast, and nearly as fast as the C++ implementation. >> There is no GC or object creation involved here, just arrays and >> computations. >> >> Without sharing some code, it's almost impossible to tell what might be the >> cause of the discrepancy or any ways to improve performance. Have you >> measured performance with the regular JITter rather than LLVM? >
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