ndslice: convert a sliced object to T[]

[Seb via Digitalmars-d-learn]

On Wednesday, 15 June 2016 at 11:19:20 UTC, data pulverizer wrote:
> On Wednesday, 15 June 2016 at 09:32:21 UTC, Andrea Fontana 
> wrote:
>> Then I think the slice.byElement.array is the right solution.
>
> The problem with that is that it slows down the code. I 
> compared matrix multiplication between R and D's cblas adaptor 
> and ndslice.
>
> n = 4000
> Matrices: A, B
> Sizes: both n by n
> Engine: both call openblas
>
> R Elapsed Time: 2.709 s
> D's cblas and ndslice: 3.593 s
>
> The R code:
>
> n = 4000; A = matrix(runif(n*n), nr = n); B = 
> matrix(runif(n*n), nr = n)
> system.time(C <- A%*%B)
>
> The D code:
>
> import std.stdio : writeln;
> import std.experimental.ndslice;
> import std.random : Random, uniform;
> import std.conv : to;
> import std.array : array;
> import cblas;
> import std.datetime : StopWatch;
>
>
> T[] runif(T)(ulong len, T min, T max){
> 	T[] arr = new T[len];
> 	Random gen;
> 	for(ulong i = 0; i < len; ++i)
> 		arr[i] = uniform(min, max, gen);
> 	return arr;
> }
>
> // Random matrix
> auto rmat(T)(ulong nrow, ulong ncol, T min, T max){
> 	return runif(nrow*ncol, min, max).sliced(nrow, ncol);
> }
>
> auto matrix_mult(T)(Slice!(2, T*) a, Slice!(2, T*) b){
> 	int M = to!int(a.shape[0]);
> 	int K = to!int(a.shape[1]);
> 	int N = to!int(b.shape[1]);
> 	int n_el = to!int(a.elementsCount);
> 	T[] A = a.byElement.array;
> 	T[] B = b.byElement.array;
> 	T[] C = new T[M*N];
> 	gemm(Order.ColMajor, Transpose.NoTrans, Transpose.NoTrans, M, 
> N, K, 1., A.ptr, K, B.ptr, N, 0, C.ptr, N);
> 	return C.sliced(M, N);
> }
>
>
> void main()
> {
> 	int n = 4000;
> 	auto A = rmat(n, n, 0., 1.);
> 	auto B = rmat(n, n, 0., 1. );
> 	StopWatch sw;
> 	sw.start();
> 	auto C = matrix_mult(A, B);
> 	sw.stop();
> 	writeln("Time taken: \n\t", sw.peek().msecs, " [ms]");
> }
>
> In my system monitor I can see the copy phase in the D process 
> as as single core process. There should be a way to do go from 
> ndslice to T[] without copying. Using a foreach loop is even 
> slower

As said you can avoid the copy (see below). I also profiled it a 
bit and it was interesting to see that 50% of the runtime are 
spent on generating the random matrix. On my machine now both 
scripts take 1.5s when compiled with

DFLAGS="-release -O3 -boundscheck=off" dub foo2.d --compiler=ldc
(`-b release` would also work)

#!/usr/bin/env dub
/+ dub.sdl:
name "matrix_mult"
dependency "cblas" version="~master"
dependency "mir" version="~>0.15"
+/
import std.stdio : writeln;
import mir.ndslice;
import std.random : Random, uniform;
import std.conv : to;
import std.array : array;
import cblas;
import std.datetime : StopWatch;


T[] runif(T)(ulong len, T min, T max){
	T[] arr = new T[len];
	Random gen;
	for(ulong i = 0; i < len; ++i)
		arr[i] = uniform(min, max, gen);
	return arr;
}

// Random matrix
auto rmat(T)(ulong nrow, ulong ncol, T min, T max){
     import std.typecons : tuple;
     auto arr = runif(nrow*ncol, min, max);
	return tuple(arr, arr.sliced(nrow, ncol));
}

auto matrix_mult(T)(T[] A, T[] B, Slice!(2, T*) a, Slice!(2, T*) 
b){
	int M = to!int(a.shape[0]);
	int K = to!int(a.shape[1]);
	int N = to!int(b.shape[1]);
	int n_el = to!int(a.elementsCount);
	T[] C = new T[M*N];
     gemm(Order.ColMajor, Transpose.NoTrans, Transpose.NoTrans, M, 
N, K, 1., A.ptr, K, B.ptr, N, 0, C.ptr, N);
	return C.sliced(M, N);
}

void main()
{
	int n = 4000;
	auto ta = rmat(n, n, 0., 1.);
	auto tb = rmat(n, n, 0., 1. );
	StopWatch sw;
	sw.start();
	auto C = matrix_mult(ta[0], tb[0], ta[1], tb[1]);
	sw.stop();
	writeln("Time taken: \n\t", sw.peek().msecs, " [ms]");
}

For performance issues, you should definitely open an issue at 
mir (the development library of ndslice): 
https://github.com/libmir/mir