portelli/Grid
1
0
Fork 0
mirror of https://github.com/paboyle/Grid.git synced 2024-11-09 23:45:36 +00:00
Code Releases Activity

Annoying hack that is useful to preserve for profiling

Browse Source
This commit is contained in:
Peter Boyle 2023-09-29 17:11:12 -04:00
parent e187bcb85c
commit c564611ba7
1 changed files with 41 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

41
Grid/threads/Accelerator.h
View File

@ -137,6 +137,18 @@ inline void cuda_mem(void)
dim3 cu_blocks ((num1+nt-1)/nt,num2,1); \ dim3 cu_blocks ((num1+nt-1)/nt,num2,1); \
LambdaApply<<<cu_blocks,cu_threads,0,computeStream>>>(num1,num2,nsimd,lambda); \ LambdaApply<<<cu_blocks,cu_threads,0,computeStream>>>(num1,num2,nsimd,lambda); \
} }
#define prof_accelerator_for2dNB( iter1, num1, iter2, num2, nsimd, ... ) \
{ \
int nt=acceleratorThreads(); \
typedef uint64_t Iterator; \
auto lambda = [=] accelerator \
(Iterator iter1,Iterator iter2,Iterator lane) mutable { \
__VA_ARGS__; \
}; \
dim3 cu_threads(nsimd,acceleratorThreads(),1); \
dim3 cu_blocks ((num1+nt-1)/nt,num2,1); \
ProfileLambdaApply<<<cu_blocks,cu_threads,0,computeStream>>>(num1,num2,nsimd,lambda); \
}
#define accelerator_for6dNB(iter1, num1, \ #define accelerator_for6dNB(iter1, num1, \
iter2, num2, \ iter2, num2, \
@ -157,6 +169,20 @@ inline void cuda_mem(void)
Lambda6Apply<<<cu_blocks,cu_threads,0,computeStream>>>(num1,num2,num3,num4,num5,num6,lambda); \ Lambda6Apply<<<cu_blocks,cu_threads,0,computeStream>>>(num1,num2,num3,num4,num5,num6,lambda); \
} }
#define accelerator_for2dNB( iter1, num1, iter2, num2, nsimd, ... ) \
{ \
int nt=acceleratorThreads(); \
typedef uint64_t Iterator; \
auto lambda = [=] accelerator \
(Iterator iter1,Iterator iter2,Iterator lane) mutable { \
__VA_ARGS__; \
}; \
dim3 cu_threads(nsimd,acceleratorThreads(),1); \
dim3 cu_blocks ((num1+nt-1)/nt,num2,1); \
LambdaApply<<<cu_blocks,cu_threads,0,computeStream>>>(num1,num2,nsimd,lambda); \
}
template<typename lambda> __global__ template<typename lambda> __global__
void LambdaApply(uint64_t num1, uint64_t num2, uint64_t num3, lambda Lambda) void LambdaApply(uint64_t num1, uint64_t num2, uint64_t num3, lambda Lambda)
{ {
@ -168,6 +194,17 @@ void LambdaApply(uint64_t num1, uint64_t num2, uint64_t num3, lambda Lambda)
Lambda(x,y,z); Lambda(x,y,z);
} }
} }
template<typename lambda> __global__
void ProfileLambdaApply(uint64_t num1, uint64_t num2, uint64_t num3, lambda Lambda)
{
// Weird permute is to make lane coalesce for large blocks
uint64_t x = threadIdx.y + blockDim.y*blockIdx.x;
uint64_t y = threadIdx.z + blockDim.z*blockIdx.y;
uint64_t z = threadIdx.x;
if ( (x < num1) && (y<num2) && (z<num3) ) {
Lambda(x,y,z);
}
}
template<typename lambda> __global__ template<typename lambda> __global__
void Lambda6Apply(uint64_t num1, uint64_t num2, uint64_t num3, void Lambda6Apply(uint64_t num1, uint64_t num2, uint64_t num3,
@ -208,6 +245,7 @@ inline void *acceleratorAllocShared(size_t bytes)
if( err != cudaSuccess ) { if( err != cudaSuccess ) {
ptr = (void *) NULL; ptr = (void *) NULL;
printf(" cudaMallocManaged failed for %d %s \n",bytes,cudaGetErrorString(err)); printf(" cudaMallocManaged failed for %d %s \n",bytes,cudaGetErrorString(err));
assert(0);
} }
return ptr; return ptr;
}; };
@ -460,6 +498,9 @@ inline void acceleratorCopySynchronise(void) { hipStreamSynchronize(copyStream);
#if defined(GRID_SYCL) || defined(GRID_CUDA) || defined(GRID_HIP) #if defined(GRID_SYCL) || defined(GRID_CUDA) || defined(GRID_HIP)
// FIXME -- the non-blocking nature got broken March 30 2023 by PAB // FIXME -- the non-blocking nature got broken March 30 2023 by PAB
#define accelerator_forNB( iter1, num1, nsimd, ... ) accelerator_for2dNB( iter1, num1, iter2, 1, nsimd, {__VA_ARGS__} ); #define accelerator_forNB( iter1, num1, nsimd, ... ) accelerator_for2dNB( iter1, num1, iter2, 1, nsimd, {__VA_ARGS__} );
#define prof_accelerator_for( iter1, num1, nsimd, ... ) \
prof_accelerator_for2dNB( iter1, num1, iter2, 1, nsimd, {__VA_ARGS__} );\
accelerator_barrier(dummy);
#define accelerator_for( iter, num, nsimd, ... ) \ #define accelerator_for( iter, num, nsimd, ... ) \
accelerator_forNB(iter, num, nsimd, { __VA_ARGS__ } ); \ accelerator_forNB(iter, num, nsimd, { __VA_ARGS__ } ); \