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// SPDX-License-Identifier: Apache-2.0
#pragma once
#include <cassert>
#include <cmath>
#include <random>
#include <algorithm>
#include <iostream>
#include "GB_cuda_reduce_factory.hpp"
#include "GpuTimer.h"
#include "GB_cuda_buckets.h"
#include "../../rmm_wrap/rmm_wrap.h"
#include <gtest/gtest.h>
#include "test_data.hpp"
#include "problem_spec.hpp"
extern "C" {
#include "GB.h"
#include "GraphBLAS.h"
}
#include "../jitFactory.hpp"
#include "dataFactory.hpp"
////Operations for test results on CPU
//template<typename T> T myOP_plus( T a, T b) { return a + b;}
//template<typename T> T myOP_min ( T a, T b) { return a < b ? a : b;}
//template<typename T> T myOP_max ( T a, T b) { return a > b ? a : b;}
//template<typename T> T myOP_first ( T a, T b) { return a ;}
//template<typename T> T myOP_second ( T a, T b) { return b ;}
//template<typename T> T myOP_times ( T a, T b) { return a * b ;}
//
//template<typename T> T (*myOpPTR)(T a, T b);
//template<typename T> T (*ADD_ptr)(T a, T b);
//template<typename T> T (*MUL_ptr)(T a, T b);
//AxB_dot3_phase1 kernels
template <typename T_C, typename T_M, typename T_A,typename T_B>
bool test_AxB_phase1_factory( int64_t , int64_t , int64_t , int64_t ) ;
//AxB_dot3_phase2 kernels
template <typename T_C>
bool test_AxB_dot3_phase2_factory( int , int64_t , int64_t , int64_t, int64_t ) ;
template<typename T>
void make_grb_matrix(GrB_Matrix mat, int64_t n_rows, int64_t n_cols,
std::vector<int64_t> &indptr,
std::vector<int64_t> &indices, T *data,
int gxb_sparsity_control = GxB_SPARSE,
int gxb_format = GxB_BY_ROW) ;
//Fixture to generate valid inputs and hold them for tests
class AxB_dot3_Test : public ::testing::Test
{
void SetUp() {}
void TearDown() {}
};
template<typename T, typename I>
void print_array(void *arr, I size, const char *name) {
std::cout << "Printing " << name << std::endl;
for(I i = 0; i < size; ++i) {
std::cout << static_cast<T*>(arr)[i] << ", ";
}
std::cout << std::endl;
}
//------------------------------------------------------------------------------
// test_AxB_phase1_factory: test phase1
//------------------------------------------------------------------------------
// Test generator code, to allow parameterized tests
// Uses jitFactory, dataFactory and GB_jit
template <typename T_C, typename T_M, typename T_A,typename T_B>
bool test_AxB_phase1_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec)
{
int gpuID;
cudaGetDevice( &gpuID);
std::cout<< "found device "<<gpuID<<std::endl;
cudaStream_t strm;
CHECK_CUDA(cudaStreamCreate(&strm));
/********************
* Launch kernel
*/
GB_cuda_mxm_factory mysemiringfactory = problem_spec.get_mxm_factory();
phase1launchFactory p1lF(mysemiringfactory);
GpuTimer kernTimer;
int nthrd = p1lF.get_threads_per_block();
int ntasks = p1lF.get_number_of_blocks(problem_spec.getM());
// TODO: Verify that RMM is checking and throwing exceptions
int nanobuckets_size = NBUCKETS * nthrd * ntasks;
int blockbuckets_size = NBUCKETS * ntasks;
int64_t *Nanobuckets = (int64_t*)rmm_wrap_malloc(nanobuckets_size * sizeof (int64_t));
int64_t *Blockbucket = (int64_t*)rmm_wrap_malloc(blockbuckets_size * sizeof (int64_t));
kernTimer.Start();
p1lF.jitGridBlockLaunch(Nanobuckets, Blockbucket,
problem_spec.getC(), problem_spec.getM(),
problem_spec.getA(), problem_spec.getB(), strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"returned from phase1 kernel "<<kernTimer.Elapsed()<<"ms"<<std::endl;
//
// print_array<int64_t>(Nanobuckets, nanobuckets_size, "Nanobuckets");
// print_array<int64_t>(Blockbucket, blockbuckets_size, "Blockbucket");
std::cout<<"==== phase1 done=============================" <<std::endl;
int64_t bucket_count = 0;
for (int i =0; i< NBUCKETS*ntasks; ++i) bucket_count += Blockbucket[i];
EXPECT_EQ( bucket_count, problem_spec.getCnnz()); //check we sum to the right structural counts
//
rmm_wrap_free(Nanobuckets);
rmm_wrap_free(Blockbucket);
std::cout << "end phase1 test ------------" << std::endl;
CHECK_CUDA(cudaStreamDestroy(strm));
fflush(stdout);
return true;
}
// Test generator code, to allow parameterized tests
// Uses jitFactory, dataFactory and GB_jit
template <typename T_C, typename T_M, typename T_A,typename T_B>
bool test_AxB_dense_phase1_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec)
{
cudaStream_t strm;
CHECK_CUDA(cudaStreamCreate(&strm));
/********************
* Launch kernel
*/
GB_cuda_mxm_factory mysemiringfactory = problem_spec.get_mxm_factory();
dense_phase1launchFactory p1lF(mysemiringfactory);
p1lF.jitGridBlockLaunch(problem_spec.getC(), problem_spec.getM(), problem_spec.getA(), problem_spec.getB(), strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
return true;
}
//------------------------------------------------------------------------------
// test_AxB_phase2_factory: test phase2 and phase2end
//------------------------------------------------------------------------------
template <typename T_C, typename T_M, typename T_A, typename T_B>
bool test_AxB_phase2_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec)
{
int gpuID;
cudaGetDevice( &gpuID);
cudaStream_t strm;
CHECK_CUDA(cudaStreamCreate(&strm));
auto mymxm = problem_spec.get_mxm_factory();
phase1launchFactory p1lF(mymxm);
phase2launchFactory p2lF;
phase2endlaunchFactory p2elF;
GpuTimer kernTimer;
kernTimer.Start();
const int64_t mnz = GB_nnz (problem_spec.getM()) ;
int nthrd = p2lF.get_threads_per_block();
int ntasks = p2elF.get_number_of_blocks(problem_spec.getM());
// fabricate data as if it came from phase1:
int64_t *nanobuckets = (int64_t*)rmm_wrap_malloc(NBUCKETS * nthrd * ntasks * sizeof (int64_t));
int64_t *blockbucket = (int64_t*)rmm_wrap_malloc(NBUCKETS * ntasks * sizeof (int64_t));
int64_t *bucketp = (int64_t*)rmm_wrap_malloc((NBUCKETS+1) * sizeof (int64_t));
int64_t *offset = (int64_t*)rmm_wrap_malloc(NBUCKETS * sizeof (int64_t));
int64_t *bucket = (int64_t*)rmm_wrap_malloc(mnz * sizeof (int64_t));
fillvector_constant(NBUCKETS, bucketp, (int64_t)0);
fillvector_constant(NBUCKETS, offset, (int64_t)0);
//fillvector_constant(problem_spec.getCnnz(), bucket, (int64_t)0);
std::cout << "Running phase1 kernel" << std::endl;
kernTimer.Start();
p1lF.jitGridBlockLaunch(nanobuckets, blockbucket,
problem_spec.getC(), problem_spec.getM(),
problem_spec.getA(), problem_spec.getB(), strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout << " phase1 internal phase2 "<< kernTimer.Elapsed() <<"ms Done." << std::endl;
// // launch phase2 (just with p2ntasks as the # of tasks)
kernTimer.Start();
p2lF.jitGridBlockLaunch(blockbucket, offset, problem_spec.getM(),strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout << " phase2 kern "<< kernTimer.Elapsed() <<"ms Done." << std::endl;
//
// // do the reduction between phase2 and phase2end
int64_t s= 0;
for ( int bucket = 0 ; bucket < NBUCKETS+1; ++bucket)
{
bucketp[bucket] = s;
s+= offset[bucket];
}
// launch phase2end: note same # of tasks as phase1
kernTimer.Start();
p2elF.jitGridBlockLaunch( nanobuckets, blockbucket,
bucketp, bucket, offset, problem_spec.getC(),
problem_spec.getM(),strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"returned from phase2end kernel "<<kernTimer.Elapsed()<<"ms"<<std::endl;
//
//
print_array<int64_t>(bucketp, NBUCKETS, "bucketp");
// print_array<int64_t>(bucket, mnz, "bucket");
std::cout<<"phase2 done =================="<<std::endl;
EXPECT_EQ( bucketp[NBUCKETS], problem_spec.getCnnz()); //check we sum to the right structural counts
rmm_wrap_free(nanobuckets);
rmm_wrap_free(blockbucket);
rmm_wrap_free(bucketp);
rmm_wrap_free(bucket);
rmm_wrap_free(offset);
CHECK_CUDA(cudaStreamDestroy(strm));
return true;
}
template<typename T>
void make_grb_matrix(GrB_Matrix mat, int64_t n_rows, int64_t n_cols,
std::vector<int64_t> &indptr,
std::vector<int64_t> &indices, T *data,
int gxb_sparsity_control,
int gxb_format )
{
GrB_Type type = cuda::jit::to_grb_type<T>();
GRB_TRY (GrB_Matrix_new (&mat, type, n_rows, n_cols)) ;
for(int64_t row = 0; row < n_rows; ++row) {
int64_t start = indptr[row];
int64_t stop = indptr[row+1];
for(int64_t offset = start; offset < stop; ++offset) {
GrB_Index i = (GrB_Index) row;
GrB_Index j = (GrB_Index) indices[offset];
T x = data[offset];
cuda::jit::set_element<T> (mat, x, i, j) ;
}
}
GRB_TRY (GrB_Matrix_wait (mat, GrB_MATERIALIZE)) ;
GRB_TRY (GB_convert_any_to_non_iso (mat, true, NULL)) ;
GRB_TRY (GxB_Matrix_Option_set (mat, GxB_SPARSITY_CONTROL, gxb_sparsity_control)) ;
GRB_TRY (GxB_Matrix_Option_set(mat, GxB_FORMAT, gxb_format));
}
template <
typename T_C, typename T_M, typename T_A,typename T_B,
typename T_X, typename T_Y, typename T_Z>
bool test_AxB_dot3_sparse_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec) {
// FIXME: Allow the adaptive tests in this guy
std::cout << "sparse test ======================" << std::endl;
GpuTimer kernTimer;
cudaStream_t strm;
CHECK_CUDA(cudaStreamCreate(&strm));
std::cout << "sr_code: " << problem_spec.get_mxm_factory().sr_code << std::endl;
bool result = false;
int64_t N = problem_spec.getN();
/**
* Run Phase 1, phase 2 and phase2end: Compute nanobuckets and blockbuckets
*/
auto mymxm = problem_spec.get_mxm_factory();
phase1launchFactory p1lF(mymxm);
phase2launchFactory p2lF;
phase2endlaunchFactory p2elF;
GrB_Matrix C = problem_spec.getC();
GrB_Matrix M = problem_spec.getM();
GrB_Matrix A = problem_spec.getA();
GrB_Matrix B = problem_spec.getB();
const int64_t mnz = GB_nnz (M) ;
const int64_t cnz = GB_nnz (C) ;
const int64_t cvlen = C->vlen ;
const int64_t cvdim = C->vdim ;
const int64_t cnvec = C->nvec ;
bool C_iso = false ;
int C_sparsity = GB_sparsity (M) ;
int M_sparsity = GB_sparsity (M) ;
GrB_Type ctype = problem_spec.getBinaryOp()->ztype ;
int nthrd = p2lF.get_threads_per_block();
int ntasks = p2elF.get_number_of_blocks(M);
// fabricate data as if it came from phase1:
int64_t *nanobuckets = (int64_t*)rmm_wrap_malloc(NBUCKETS * nthrd * ntasks * sizeof (int64_t));
int64_t *blockbucket = (int64_t*)rmm_wrap_malloc(NBUCKETS * ntasks * sizeof (int64_t));
int64_t *bucketp = (int64_t*)rmm_wrap_malloc((NBUCKETS+1) * sizeof (int64_t));
int64_t *bucket = (int64_t*)rmm_wrap_malloc(mnz * sizeof (int64_t));
int64_t *offset = (int64_t*)rmm_wrap_malloc(NBUCKETS * sizeof (int64_t));
fillvector_constant(NBUCKETS, bucketp, (int64_t)0);
fillvector_constant(NBUCKETS, offset, (int64_t)0);
//fillvector_constant(problem_spec.getCnnz(), bucket, (int64_t)0);
std::cout << "sparse phase1 kernel" << std::endl;
kernTimer.Start();
p1lF.jitGridBlockLaunch(nanobuckets, blockbucket,
C, M, A, B, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"sparse test phase1 kernel "<<kernTimer.Elapsed()<<"ms"<<std::endl;
// // launch phase2 (just with p2ntasks as the # of tasks)
kernTimer.Start();
p2lF.jitGridBlockLaunch(blockbucket, offset, M, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"sparse test phase2 kernel "<<kernTimer.Elapsed()<<"ms"<<std::endl;
//
// // do the reduction between phase2 and phase2end
int64_t s= 0;
for ( int bucket = 0 ; bucket < NBUCKETS+1; ++bucket)
{
bucketp[bucket] = s;
s+= offset[bucket];
}
std::cout << "Launching phase2end" << std::endl;
// launch phase2end: note same # of tasks as phase1
kernTimer.Start();
p2elF.jitGridBlockLaunch( nanobuckets, blockbucket,
bucketp, bucket, offset, C, M, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout << "sparse test phase2end " <<kernTimer.Elapsed()<<"ms"<<std::endl;
/**
* Run Phase 3: Execute dot3 on all buckets
*/
for (int b = 1; b < NBUCKETS; ++b) {// loop on buckets
int64_t b_start = bucketp[b];
int64_t b_end = bucketp[b+1];
int64_t nvecs = b_end - b_start;
if (nvecs == 0) continue;
kernTimer.Start();
phase3launchFactory p3lf(mymxm, (GB_bucket_code)b);
p3lf.jitGridBlockLaunch( b_start, b_end, bucketp, bucket, C, M,
A, B, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout << "phase3 bucket="<<b<<" done " <<kernTimer.Elapsed()<<"ms"<<std::endl;
fflush(stdout);
}
C->nzombies += (bucketp[1]); //add pre-zombies to the count;
GRB_TRY(GrB_Matrix_wait(C, GrB_MATERIALIZE));
fflush(stdout);
GrB_Matrix C_expected;
GrB_Type type = cuda::jit::to_grb_type<T_C>();
GRB_TRY (GrB_Matrix_new (&C_expected, type, N, N)) ;
// ensure the GPU is not used
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_NEVER)) ;
// Use GrB_DESC_S for structural because dot3 mask will never be complemented
// The order of B and A is swapped to account for CSR vs CSC assumption
GRB_TRY (GrB_mxm(C_expected, problem_spec.getM(), NULL, problem_spec.get_semiring(), problem_spec.getB(),
problem_spec.getA(), problem_spec.get_mask_struct() ? GrB_DESC_ST1 : GrB_DESC_T1));
GRB_TRY(GrB_Matrix_wait(C_expected, GrB_MATERIALIZE));
// compare
double tol = 0 ;
GrB_Index nvals1 = 0, nvals2 = 0 ;
GRB_TRY (GrB_Matrix_nvals (&nvals1, C)) ;
GRB_TRY (GrB_Matrix_nvals (&nvals2, C_expected)) ;
if (nvals1 != nvals2) { printf ("Wrong number of nonzeroes found, test fail!!!\n") ; ADD_FAILURE( ) ; }
GrB_Index nrows, ncols ;
GrB_Matrix_nrows (&nrows, C_expected) ;
GrB_Matrix_ncols (&ncols, C_expected) ;
GrB_Matrix T;
GRB_TRY (GrB_Matrix_new (&T, GrB_BOOL, nrows, ncols)) ;
GrB_BinaryOp op = NULL;
GrB_UnaryOp op_abs = NULL ;
if (type == GrB_BOOL ) op = GrB_EQ_BOOL ;
else if (type == GrB_INT8 ) op = GrB_EQ_INT8 ;
else if (type == GrB_INT16 ) op = GrB_EQ_INT16 ;
else if (type == GrB_INT32 ) op = GrB_EQ_INT32 ;
else if (type == GrB_INT64 ) op = GrB_EQ_INT64 ;
else if (type == GrB_UINT8 ) op = GrB_EQ_UINT8 ;
else if (type == GrB_UINT16) op = GrB_EQ_UINT16 ;
else if (type == GrB_UINT32) op = GrB_EQ_UINT32 ;
else if (type == GrB_UINT64) op = GrB_EQ_UINT64 ;
else if (type == GrB_FP32 )
{ tol = 1e-6;
op = (tol == 0)? GrB_EQ_FP32 : GrB_MINUS_FP32 ;
op_abs = GrB_ABS_FP32 ;
}
else if (type == GrB_FP64 )
{ tol = 1e12;
op = (tol == 0)? GrB_EQ_FP64 : GrB_MINUS_FP64 ;
op_abs = GrB_ABS_FP64 ;
}
else if (type == GxB_FC32 )
{ tol = 2e-6;
op = (tol == 0)? GxB_EQ_FC32 : GxB_MINUS_FC32 ;
op_abs = GxB_ABS_FC32 ;
}
else if (type == GxB_FC64 )
{ tol = 2e-12;
op = (tol == 0)? GxB_EQ_FC64 : GxB_MINUS_FC64 ;
op_abs = GxB_ABS_FC64 ;
}
if (tol == 0)
{
// check for perfect equality
GRB_TRY (GrB_Matrix_eWiseMult_BinaryOp (T, NULL, NULL, op, C, C_expected,
NULL)) ;
GrB_Index nvals3 = 1 ;
GRB_TRY (GrB_Matrix_nvals (&nvals3, T)) ;
// if (nvals1 != nvals3) { printf (" difference matrix wrong size, test fail!!\n") ; ADD_FAILURE( ) ; }
bool is_same = false ;
GRB_TRY (GrB_Matrix_reduce_BOOL (&is_same, NULL, GrB_LAND_MONOID_BOOL,
T, NULL)) ;
if (!is_same) { printf (" results don't match, test fail!!\n") ; ADD_FAILURE ( ) ; }
GRB_TRY (GrB_Matrix_free (&T)) ;
}
else
{
// TODO: check with roundoff
// Diff = C - C_expected
GrB_Matrix Diff ;
GRB_TRY (GrB_Matrix_new (&Diff, GrB_FP64, nrows, ncols)) ;
GRB_TRY (GrB_Matrix_apply (Diff, NULL, NULL, GrB_AINV_FP64, C_expected, NULL)) ;
GRB_TRY (GrB_Matrix_eWiseAdd_BinaryOp (Diff, NULL, NULL, GrB_PLUS_FP64,
C, Diff, NULL)) ;
GRB_TRY( GrB_Matrix_apply( Diff, NULL, NULL, op_abs, Diff, NULL) );
GrB_Index nvals3 = 1 ;
GRB_TRY (GrB_Matrix_nvals (&nvals3, Diff)) ;
if (nvals1 != nvals3) { printf ("fp difference matrix wrong size, test fail!!\n") ; ADD_FAILURE( ) ; }
double is_same = false ;
GRB_TRY (GrB_Matrix_reduce_FP64 (&is_same, NULL, GrB_PLUS_MONOID_FP64,
Diff, NULL)) ;
printf("difference = %12.6g, rel_l1_err=%12.6g\n", is_same, is_same/nvals3 );
EXPECT_LT( is_same/nvals3, tol);
GRB_TRY (GrB_Matrix_free (&Diff)) ;
}
// re-enable the GPU
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_ALWAYS)) ;
rmm_wrap_free(nanobuckets);
rmm_wrap_free(blockbucket);
rmm_wrap_free(bucketp);
rmm_wrap_free(bucket);
rmm_wrap_free(offset);
GRB_TRY(GrB_Matrix_free(&C_expected));
CHECK_CUDA(cudaStreamDestroy(strm));
std::cout << "phase 3 test complete ======================" << std::endl;
return result;
}
template <
typename T_C, typename T_M, typename T_A,typename T_B,
typename T_X, typename T_Y, typename T_Z>
bool test_AxB_dot3_dense_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec) {
std::cout << "phase dense test ======================" << std::endl;
GpuTimer kernTimer;
cudaStream_t strm;
CHECK_CUDA(cudaStreamCreate(&strm));
bool result = false;
int64_t N = problem_spec.getN();
auto mymxm = problem_spec.get_mxm_factory();
dense_phase1launchFactory p1lF(mymxm);
GrB_Matrix C = problem_spec.getC();
GrB_Matrix M = problem_spec.getM();
GrB_Matrix A = problem_spec.getA();
GrB_Matrix B = problem_spec.getB();
problem_spec.set_sparsity_control( A, GxB_FULL, GxB_BY_ROW);
problem_spec.set_sparsity_control( B, GxB_FULL, GxB_BY_ROW);
const int64_t mnz = GB_nnz (M) ;
const int64_t cnz = GB_nnz (C) ;
const int64_t cvlen = C->vlen ;
const int64_t cvdim = C->vdim ;
const int64_t cnvec = C->nvec ;
bool C_iso = false ;
GrB_Type ctype = problem_spec.getBinaryOp()->ztype ;
std::cout << "Running phase1 kernel" << std::endl;
kernTimer.Start();
p1lF.jitGridBlockLaunch(C, M, A, B, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"Dense internal phase1 kernel done "<<kernTimer.Elapsed()<<"ms"<<std::endl;
std::cout << "Running dense kernel" << std::endl;
mxm_dense_launchFactory p3lf(mymxm);
kernTimer.Start();
p3lf.jitGridBlockLaunch( C, M, A, B, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"Dense kernel done "<<kernTimer.Elapsed()<<"ms"<<std::endl;
GRB_TRY(GrB_Matrix_wait(C, GrB_MATERIALIZE));
fflush(stdout);
GrB_Matrix C_expected;
GrB_Type type = cuda::jit::to_grb_type<T_C>();
GRB_TRY (GrB_Matrix_new (&C_expected, type, N, N)) ;
// ensure the GPU is not used
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_NEVER)) ;
// Use GrB_DESC_S for structural because dot3 mask will never be complemented
// The order of B and A is swapped to account for CSR vs CSC assumption
GRB_TRY (GrB_mxm(C_expected, problem_spec.getM(), NULL, problem_spec.get_semiring(), problem_spec.getB(),
problem_spec.getA(), problem_spec.get_mask_struct() ? GrB_DESC_ST1 : GrB_DESC_T1));
GRB_TRY(GrB_Matrix_wait(C_expected, GrB_MATERIALIZE));
std::cout << "nnz: " << GB_nnz (C_expected) << std::endl ;
// compare
double tol = 0 ;
GrB_Index nvals1 = 0, nvals2 = 0 ;
GRB_TRY (GrB_Matrix_nvals (&nvals1, C)) ;
GRB_TRY (GrB_Matrix_nvals (&nvals2, C_expected)) ;
if (nvals1 != nvals2) { printf ("Wrong number of nonzeroes found, test fail!!! nvals1=%lu, nvals2=%lu\n", nvals1, nvals2) ; ADD_FAILURE( ) ; }
GrB_Index nrows, ncols ;
GrB_Matrix_nrows (&nrows, C_expected) ;
GrB_Matrix_ncols (&ncols, C_expected) ;
GrB_Matrix T;
GRB_TRY (GrB_Matrix_new (&T, GrB_BOOL, nrows, ncols)) ;
GrB_BinaryOp op = NULL;
GrB_UnaryOp op_abs = NULL ;
if (type == GrB_BOOL ) op = GrB_EQ_BOOL ;
else if (type == GrB_INT8 ) op = GrB_EQ_INT8 ;
else if (type == GrB_INT16 ) op = GrB_EQ_INT16 ;
else if (type == GrB_INT32 ) op = GrB_EQ_INT32 ;
else if (type == GrB_INT64 ) op = GrB_EQ_INT64 ;
else if (type == GrB_UINT8 ) op = GrB_EQ_UINT8 ;
else if (type == GrB_UINT16) op = GrB_EQ_UINT16 ;
else if (type == GrB_UINT32) op = GrB_EQ_UINT32 ;
else if (type == GrB_UINT64) op = GrB_EQ_UINT64 ;
else if (type == GrB_FP32 )
{ tol = 5e-6;
op = (tol == 0)? GrB_EQ_FP32 : GrB_MINUS_FP32 ;
op_abs = GrB_ABS_FP32 ;
}
else if (type == GrB_FP64 )
{ tol = 1e12;
op = (tol == 0)? GrB_EQ_FP64 : GrB_MINUS_FP64 ;
op_abs = GrB_ABS_FP64 ;
}
else if (type == GxB_FC32 )
{ tol = 2e-6;
op = (tol == 0)? GxB_EQ_FC32 : GxB_MINUS_FC32 ;
op_abs = GxB_ABS_FC32 ;
}
else if (type == GxB_FC64 )
{ tol = 2e-12;
op = (tol == 0)? GxB_EQ_FC64 : GxB_MINUS_FC64 ;
op_abs = GxB_ABS_FC64 ;
}
if (tol == 0)
{
// check for perfect equality
GRB_TRY (GrB_Matrix_eWiseMult_BinaryOp (T, NULL, NULL, op, C, C_expected,
NULL)) ;
GrB_Index nvals3 = 1 ;
GRB_TRY (GrB_Matrix_nvals (&nvals3, T)) ;
// if (nvals1 != nvals3) { printf (" difference matrix wrong size, test fail!! nvals1=%ld nvals3=%ld\n", nvals1, nvals3) ; ADD_FAILURE( ) ; }
bool is_same = false ;
GRB_TRY (GrB_Matrix_reduce_BOOL (&is_same, NULL, GrB_LAND_MONOID_BOOL,
T, NULL)) ;
if (!is_same) { printf (" results don't match, test fail!!\n") ; ADD_FAILURE ( ) ; }
GRB_TRY (GrB_Matrix_free (&T)) ;
}
else
{
// TODO: check with roundoff
// Diff = C - C_expected
GrB_Matrix Diff ;
GRB_TRY (GrB_Matrix_new (&Diff, GrB_FP64, nrows, ncols)) ;
GRB_TRY (GrB_Matrix_apply (Diff, NULL, NULL, GrB_AINV_FP64, C_expected, NULL)) ;
GRB_TRY (GrB_Matrix_eWiseAdd_BinaryOp (Diff, NULL, NULL, GrB_PLUS_FP64,
C, Diff, NULL)) ;
GRB_TRY( GrB_Matrix_apply( Diff, NULL, NULL, op_abs, Diff, NULL) );
GrB_Index nvals3 = 1 ;
GRB_TRY (GrB_Matrix_nvals (&nvals3, Diff)) ;
if (nvals1 != nvals3) { printf ("fp difference matrix wrong size, test fail!!\n") ; ADD_FAILURE( ) ; }
double is_same = false ;
GRB_TRY (GrB_Matrix_reduce_FP64 (&is_same, NULL, GrB_PLUS_MONOID_FP64,
Diff, NULL)) ;
printf("difference = %12.6g, rel_l1_err=%12.6g\n", is_same, is_same/nvals3 );
EXPECT_LT( is_same/nvals3, tol);
GRB_TRY (GrB_Matrix_free (&Diff)) ;
}
// re-enable the GPU
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_ALWAYS)) ;
GRB_TRY(GrB_Matrix_free(&C_expected));
CHECK_CUDA(cudaStreamDestroy(strm));
std::cout << "phase 3 dense test complete ======================" << std::endl;
return result;
}
template <
typename T_C, typename T_M, typename T_A,typename T_B,
typename T_X, typename T_Y, typename T_Z>
bool test_AxB_dot3_sparse_dense_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec) {
std::cout << "sparse dense test ======================" << std::endl;
GpuTimer kernTimer;
cudaStream_t strm;
CHECK_CUDA(cudaStreamCreate(&strm));
bool result = false;
int64_t N = problem_spec.getN();
GrB_Matrix C = problem_spec.getC();
GrB_Matrix M = problem_spec.getM();
GrB_Matrix A = problem_spec.getA();
GrB_Matrix B = problem_spec.getB();
problem_spec.set_sparsity_control( A, GxB_SPARSE, GxB_BY_ROW);
// TODO: Need to make sure the format itself is actually dense.
problem_spec.set_sparsity_control( B, GxB_FULL, GxB_BY_ROW);
auto mymxm = problem_spec.get_mxm_factory();
dense_phase1launchFactory p1lF(mymxm);
const int64_t mnz = GB_nnz (M) ;
const int64_t cnz = GB_nnz (C) ;
const int64_t cvlen = C->vlen ;
const int64_t cvdim = C->vdim ;
const int64_t cnvec = C->nvec ;
bool C_iso = false ;
GrB_Type ctype = problem_spec.getBinaryOp()->ztype ;
std::cout << "Running dense_phase1 kernel" << std::endl;
kernTimer.Start();
p1lF.jitGridBlockLaunch(C, M, A, B, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"Dense internal phase1 kernel done "<<kernTimer.Elapsed()<<"ms"<<std::endl;
std::cout << "Running sparse dense kernel" << std::endl;
mxm_sparse_dense_launchFactory spdnlf(mymxm);
kernTimer.Start();
spdnlf.jitGridBlockLaunch( C, M, A, B, strm);
CHECK_CUDA(cudaStreamSynchronize(strm));
kernTimer.Stop();
std::cout<<"Sparse_Dense done "<<kernTimer.Elapsed()<<"ms"<<std::endl;
GRB_TRY(GrB_Matrix_wait(C, GrB_MATERIALIZE));
fflush(stdout);
GrB_Matrix C_expected;
GrB_Type type = cuda::jit::to_grb_type<T_C>();
GRB_TRY (GrB_Matrix_new (&C_expected, type, N, N)) ;
// ensure the GPU is not used
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_NEVER)) ;
// Use GrB_DESC_S for structural because dot3 mask will never be complemented
// The order of B and A is swapped to account for CSR vs CSC assumption
GRB_TRY (GrB_mxm(C_expected, problem_spec.getM(), NULL, problem_spec.get_semiring(), problem_spec.getB(),
problem_spec.getA(), problem_spec.get_mask_struct() ? GrB_DESC_ST1 : GrB_DESC_T1));
GRB_TRY(GrB_Matrix_wait(C_expected, GrB_MATERIALIZE));
std::cout << "nnz: " << GB_nnz (C_expected) << std::endl ;
// compare
double tol = 0 ;
GrB_Index nvals1 = 0, nvals2 = 0 ;
GRB_TRY (GrB_Matrix_nvals (&nvals1, C)) ;
GRB_TRY (GrB_Matrix_nvals (&nvals2, C_expected)) ;
if (nvals1 != nvals2) { printf ("Wrong number of nonzeroes found, test fail!!! nvals1=%lu, nvals2=%lu\n", nvals1, nvals2) ; ADD_FAILURE( ) ; }
GrB_Index nrows, ncols ;
GrB_Matrix_nrows (&nrows, C_expected) ;
GrB_Matrix_ncols (&ncols, C_expected) ;
GrB_Matrix T;
GRB_TRY (GrB_Matrix_new (&T, GrB_BOOL, nrows, ncols)) ;
GrB_BinaryOp op = NULL;
GrB_UnaryOp op_abs = NULL ;
if (type == GrB_BOOL ) op = GrB_EQ_BOOL ;
else if (type == GrB_INT8 ) op = GrB_EQ_INT8 ;
else if (type == GrB_INT16 ) op = GrB_EQ_INT16 ;
else if (type == GrB_INT32 ) op = GrB_EQ_INT32 ;
else if (type == GrB_INT64 ) op = GrB_EQ_INT64 ;
else if (type == GrB_UINT8 ) op = GrB_EQ_UINT8 ;
else if (type == GrB_UINT16) op = GrB_EQ_UINT16 ;
else if (type == GrB_UINT32) op = GrB_EQ_UINT32 ;
else if (type == GrB_UINT64) op = GrB_EQ_UINT64 ;
else if (type == GrB_FP32 )
{ tol = 5e-6;
op = (tol == 0)? GrB_EQ_FP32 : GrB_MINUS_FP32 ;
op_abs = GrB_ABS_FP32 ;
}
else if (type == GrB_FP64 )
{ tol = 1e12;
op = (tol == 0)? GrB_EQ_FP64 : GrB_MINUS_FP64 ;
op_abs = GrB_ABS_FP64 ;
}
else if (type == GxB_FC32 )
{ tol = 2e-6;
op = (tol == 0)? GxB_EQ_FC32 : GxB_MINUS_FC32 ;
op_abs = GxB_ABS_FC32 ;
}
else if (type == GxB_FC64 )
{ tol = 2e-12;
op = (tol == 0)? GxB_EQ_FC64 : GxB_MINUS_FC64 ;
op_abs = GxB_ABS_FC64 ;
}
if (tol == 0)
{
// check for perfect equality
GRB_TRY (GrB_Matrix_eWiseMult_BinaryOp (T, NULL, NULL, op, C, C_expected,
NULL)) ;
GrB_Index nvals3 = 1 ;
GRB_TRY (GrB_Matrix_nvals (&nvals3, T)) ;
// if (nvals1 != nvals3) { printf (" difference matrix wrong size, test fail!! nvals1=%ld nvals3=%ld\n", nvals1, nvals3) ; ADD_FAILURE( ) ; }
bool is_same = false ;
GRB_TRY (GrB_Matrix_reduce_BOOL (&is_same, NULL, GrB_LAND_MONOID_BOOL,
T, NULL)) ;
if (!is_same) { printf (" results don't match, test fail!!\n") ; ADD_FAILURE ( ) ; }
GRB_TRY (GrB_Matrix_free (&T)) ;
}
else
{
// TODO: check with roundoff
// Diff = C - C_expected
GrB_Matrix Diff ;
GRB_TRY (GrB_Matrix_new (&Diff, GrB_FP64, nrows, ncols)) ;
GRB_TRY (GrB_Matrix_apply (Diff, NULL, NULL, GrB_AINV_FP64, C_expected, NULL)) ;
GRB_TRY (GrB_Matrix_eWiseAdd_BinaryOp (Diff, NULL, NULL, GrB_PLUS_FP64,
C, Diff, NULL)) ;
GRB_TRY( GrB_Matrix_apply( Diff, NULL, NULL, op_abs, Diff, NULL) );
GrB_Index nvals3 = 1 ;
GRB_TRY (GrB_Matrix_nvals (&nvals3, Diff)) ;
if (nvals1 != nvals3) { printf ("fp difference matrix wrong size, test fail!!\n") ; ADD_FAILURE( ) ; }
double is_same = false ;
GRB_TRY (GrB_Matrix_reduce_FP64 (&is_same, NULL, GrB_PLUS_MONOID_FP64,
Diff, NULL)) ;
printf("difference = %12.6g, rel_l1_err=%12.6g\n", is_same, is_same/nvals3 );
EXPECT_LT( is_same/nvals3, tol);
GRB_TRY (GrB_Matrix_free (&Diff)) ;
}
// re-enable the GPU
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_ALWAYS)) ;
GRB_TRY(GrB_Matrix_free(&C_expected));
CHECK_CUDA(cudaStreamDestroy(strm));
std::cout << "phase 3 dense test complete ======================" << std::endl;
return result;
}
template <typename T_C, typename T_M, typename T_A, typename T_B>
bool test_reduce_factory(mxm_problem_spec<T_C, T_M, T_A, T_B> &problem_spec) {
std::cout << "reduce test ======================" << std::endl;
// TODO: This test doesn't really fit the `mxm` category
GrB_Monoid monoid = problem_spec.getMonoid();
int64_t N = problem_spec.getN();
GrB_Matrix A;
// TODO: Using C here so that the reduced type matches
GrB_Matrix_dup(&A, problem_spec.getC());
GrB_Type type = cuda::jit::to_grb_type<T_C>();
A->i[0] = GB_FLIP(A->i[0]); // FIXME
A->i[1] = GB_FLIP(A->i[1]); // FIXME
A->nzombies = 2; // FIXME: use an opaque method to insert zombies into A
//GRB_TRY (GxB_Matrix_fprint (A, "A", GxB_SHORT_VERBOSE, stdout)) ;
GB_cuda_reduce_factory myreducefactory;
myreducefactory.reduce_factory(monoid, A);
T_C actual;
GB_cuda_reduce(myreducefactory, A, &actual, monoid );
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_NEVER)) ;
T_C expected;
GRB_TRY(cuda::jit::matrix_reduce(&expected, A, monoid));
GRB_TRY (GxB_Global_Option_set (GxB_GLOBAL_GPU_CONTROL, GxB_GPU_ALWAYS)) ;
double tol = 0;
GrB_BinaryOp op = NULL;
GrB_UnaryOp op_abs = NULL ;
if (type == GrB_BOOL ) op = GrB_EQ_BOOL ;
else if (type == GrB_INT8 ) op = GrB_EQ_INT8 ;
else if (type == GrB_INT16 ) op = GrB_EQ_INT16 ;
else if (type == GrB_INT32 ) op = GrB_EQ_INT32 ;
else if (type == GrB_INT64 ) op = GrB_EQ_INT64 ;
else if (type == GrB_UINT8 ) op = GrB_EQ_UINT8 ;
else if (type == GrB_UINT16) op = GrB_EQ_UINT16 ;
else if (type == GrB_UINT32) op = GrB_EQ_UINT32 ;
else if (type == GrB_UINT64) op = GrB_EQ_UINT64 ;
else if (type == GrB_FP32 )
{ tol = 1e-6;
op = (tol == 0)? GrB_EQ_FP32 : GrB_MINUS_FP32 ;
op_abs = GrB_ABS_FP32 ;
}
else if (type == GrB_FP64 )
{ tol = 1e12;
op = (tol == 0)? GrB_EQ_FP64 : GrB_MINUS_FP64 ;
op_abs = GrB_ABS_FP64 ;
}
else if (type == GxB_FC32 )
{ tol = 2e-6;
op = (tol == 0)? GxB_EQ_FC32 : GxB_MINUS_FC32 ;
op_abs = GxB_ABS_FC32 ;
}
else if (type == GxB_FC64 )
{ tol = 2e-12;
op = (tol == 0)? GxB_EQ_FC64 : GxB_MINUS_FC64 ;
op_abs = GxB_ABS_FC64 ;
}
if(tol == 0) {
EXPECT_EQ( actual , expected);
//std::cout << "results do not match: reduced=" << expected << ", actual=" << actual << std::endl;
//exit(1);
} else if ( (tol > 0) && ( ( type ==GrB_FP32) || ( type ==GxB_FC32)
|| ( type ==GrB_FP64) || ( type ==GxB_FC64) ) ){
EXPECT_LT( abs((double)actual - (double)expected)/(abs((double)expected)+1.e-12), tol) ;
}
std::cout<< expected<< " " << actual<< "reduce test complete ======================" << std::endl;
GRB_TRY(GrB_Matrix_free(&A));
return expected == actual;
}
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