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/* StarPU --- Runtime system for heterogeneous multicore architectures.
*
* Copyright (C) 2010 Université de Bordeaux 1
* Copyright (C) 2010 Centre National de la Recherche Scientifique
*
* StarPU is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation; either version 2.1 of the License, or (at
* your option) any later version.
*
* StarPU is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
*
* See the GNU Lesser General Public License in COPYING.LGPL for more details.
*/
#include <starpu.h>
#include <starpu_cuda.h>
#include "cg.h"
#define MAXNBLOCKS 128
#define MAXTHREADSPERBLOCK 256
static __global__ void dot_device(TYPE *vx, TYPE *vy, unsigned n, TYPE *dot_array)
{
__shared__ TYPE scnt[MAXTHREADSPERBLOCK];
/* Do we have a successful shot ? */
const int tid = threadIdx.x + blockIdx.x*blockDim.x;
const int nthreads = gridDim.x * blockDim.x;
/* Blank the shared mem buffer */
if (threadIdx.x < MAXTHREADSPERBLOCK)
scnt[threadIdx.x] = (TYPE)0.0;
__syncthreads();
int ind;
for (ind = tid; ind < n; ind += nthreads)
{
TYPE x = vx[ind];
TYPE y = vy[ind];
scnt[threadIdx.x] += (x*y);
}
__syncthreads();
/* Perform a reduction to compute the sum on each thread within that block */
/* NB: We assume that the number of threads per block is a power of 2 ! */
unsigned s;
for (s = blockDim.x/2; s!=0; s>>=1)
{
if (threadIdx.x < s)
scnt[threadIdx.x] += scnt[threadIdx.x + s];
__syncthreads();
}
/* report the number of successful shots in the block */
if (threadIdx.x == 0)
dot_array[blockIdx.x] = scnt[0];
__syncthreads();
}
static __global__ void gather_dot_device(TYPE *dot_array, TYPE *dot)
{
__shared__ TYPE accumulator[MAXNBLOCKS];
unsigned i;
/* Load the values from global mem */
for (i = 0; i < blockDim.x; i++)
accumulator[i] = dot_array[i];
__syncthreads();
/* Perform a reduction in shared memory */
unsigned s;
for (s = blockDim.x/2; s!=0; s>>=1)
{
if (threadIdx.x < s)
accumulator[threadIdx.x] += accumulator[threadIdx.x + s];
__syncthreads();
}
/* Save the result in global memory */
if (threadIdx.x == 0)
*dot = *dot + accumulator[0];
}
extern "C" void dot_host(TYPE *x, TYPE *y, unsigned nelems, TYPE *dot)
{
/* How many blocks do we use ? */
unsigned nblocks = 128; // TODO
STARPU_ASSERT(nblocks <= MAXNBLOCKS);
TYPE *per_block_sum;
cudaMalloc((void **)&per_block_sum, nblocks*sizeof(TYPE));
STARPU_ASSERT((nelems % nblocks) == 0);
/* How many threads per block ? At most 256, but no more threads than
* there are entries to process per block. */
unsigned nthread_per_block = STARPU_MIN(MAXTHREADSPERBLOCK, (nelems / nblocks));
/* each entry of per_block_sum contains the number of successful shots
* in the corresponding block. */
dot_device<<<nblocks, nthread_per_block, 0, starpu_cuda_get_local_stream()>>>(x, y, nelems, per_block_sum);
/* Note that we do not synchronize between kernel calls because there
* is an implicit serialization */
gather_dot_device<<<1, nblocks, 0, starpu_cuda_get_local_stream()>>>(per_block_sum, dot);
cudaError_t cures;
cures = cudaStreamSynchronize(starpu_cuda_get_local_stream());
if (cures)
STARPU_CUDA_REPORT_ERROR(cures);
cudaFree(per_block_sum);
}
static __global__ void zero_vector_device(TYPE *x, unsigned nelems, unsigned nelems_per_thread)
{
unsigned i;
unsigned first_i = blockDim.x * blockIdx.x + threadIdx.x;
for (i = first_i; i < nelems; i += nelems_per_thread)
x[i] = 0.0;
}
extern "C" void zero_vector(TYPE *x, unsigned nelems)
{
unsigned nblocks = STARPU_MIN(128, nelems);
unsigned nthread_per_block = STARPU_MIN(MAXTHREADSPERBLOCK, (nelems / nblocks));
unsigned nelems_per_thread = nelems / (nblocks * nthread_per_block);
zero_vector_device<<<nblocks, nthread_per_block, 0, starpu_cuda_get_local_stream()>>>(x, nelems, nelems_per_thread);
}
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