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/* ************************************************************************
* Copyright (C) 2023 Advanced Micro Devices, Inc.
* ************************************************************************ */
#pragma once
#include "clientcommon.hpp"
template <typename T>
void csrrf_solve_checkBadArgs(hipsolverRfHandle_t handle,
const int n,
const int nrhs,
const int nnzT,
int* ptrT,
int* indT,
T valT,
int* pivP,
int* pivQ,
T work,
const int ldw,
T B,
const int ldb)
{
// handle
EXPECT_ROCBLAS_STATUS(hipsolverRfSolve(nullptr, pivP, pivQ, nrhs, work, ldw, B, ldb),
HIPSOLVER_STATUS_NOT_INITIALIZED);
}
template <typename T>
void testing_csrrf_solve_bad_arg()
{
// safe arguments
hipsolverRf_local_handle handle;
int n = 1;
int nrhs = 1;
int nnzT = 1;
int ldb = 1;
// memory allocations
device_strided_batch_vector<int> ptrT(1, 1, 1, 1);
device_strided_batch_vector<int> indT(1, 1, 1, 1);
device_strided_batch_vector<T> valT(1, 1, 1, 1);
device_strided_batch_vector<int> pivP(1, 1, 1, 1);
device_strided_batch_vector<int> pivQ(1, 1, 1, 1);
device_strided_batch_vector<T> B(1, 1, 1, 1);
CHECK_HIP_ERROR(ptrT.memcheck());
CHECK_HIP_ERROR(indT.memcheck());
CHECK_HIP_ERROR(valT.memcheck());
CHECK_HIP_ERROR(pivP.memcheck());
CHECK_HIP_ERROR(pivQ.memcheck());
CHECK_HIP_ERROR(B.memcheck());
int size_W = n * nrhs;
device_strided_batch_vector<T> dWork(size_W, 1, size_W, 1);
if(size_W)
CHECK_HIP_ERROR(dWork.memcheck());
// check bad arguments
csrrf_solve_checkBadArgs(handle,
n,
nrhs,
nnzT,
ptrT.data(),
indT.data(),
valT.data(),
pivP.data(),
pivQ.data(),
dWork.data(),
n,
B.data(),
ldb);
}
template <bool CPU, bool GPU, typename T, typename Td, typename Ud, typename Th, typename Uh>
void csrrf_solve_initData(hipsolverRfHandle_t handle,
const int n,
const int nrhs,
const int nnzA,
Ud& dptrA,
Ud& dindA,
Td& dvalA,
const int nnzL,
Ud& dptrL,
Ud& dindL,
Td& dvalL,
const int nnzU,
Ud& dptrU,
Ud& dindU,
Td& dvalU,
Ud& dpivP,
Ud& dpivQ,
Td& dB,
const int ldb,
Uh& hptrA,
Uh& hindA,
Th& hvalA,
Uh& hptrL,
Uh& hindL,
Th& hvalL,
Uh& hptrU,
Uh& hindU,
Th& hvalU,
Uh& hpivP,
Uh& hpivQ,
Th& hB,
Th& hX,
const fs::path testcase,
bool test = true)
{
if(CPU)
{
fs::path file;
std::string filename;
// read-in A
file = testcase / "ptrA";
read_matrix(file.string(), 1, n + 1, hptrA.data(), 1);
file = testcase / "indA";
read_matrix(file.string(), 1, nnzA, hindA.data(), 1);
file = testcase / "valA";
read_matrix(file.string(), 1, nnzA, hvalA.data(), 1);
// read-in L
file = testcase / "ptrL";
read_matrix(file.string(), 1, n + 1, hptrL.data(), 1);
file = testcase / "indL";
read_matrix(file.string(), 1, nnzL, hindL.data(), 1);
file = testcase / "valL";
read_matrix(file.string(), 1, nnzL, hvalL.data(), 1);
// read-in U
file = testcase / "ptrU";
read_matrix(file.string(), 1, n + 1, hptrU.data(), 1);
file = testcase / "indU";
read_matrix(file.string(), 1, nnzU, hindU.data(), 1);
file = testcase / "valU";
read_matrix(file.string(), 1, nnzU, hvalU.data(), 1);
// read-in P
file = testcase / "P";
read_matrix(file.string(), 1, n, hpivP.data(), 1);
// read-in Q
file = testcase / "Q";
read_matrix(file.string(), 1, n, hpivQ.data(), 1);
// read-in B
filename = std::string("B_") + std::to_string(nrhs);
file = testcase / filename;
read_matrix(file.string(), n, nrhs, hB.data(), ldb);
// get results (matrix X) if validation is required
if(test)
{
// read-in X
filename = std::string("X_") + std::to_string(nrhs);
file = testcase / filename;
read_matrix(file.string(), n, nrhs, hX.data(), ldb);
}
}
if(GPU)
{
CHECK_HIP_ERROR(dptrA.transfer_from(hptrA));
CHECK_HIP_ERROR(dindA.transfer_from(hindA));
CHECK_HIP_ERROR(dvalA.transfer_from(hvalA));
CHECK_HIP_ERROR(dptrL.transfer_from(hptrL));
CHECK_HIP_ERROR(dindL.transfer_from(hindL));
CHECK_HIP_ERROR(dvalL.transfer_from(hvalL));
CHECK_HIP_ERROR(dptrU.transfer_from(hptrU));
CHECK_HIP_ERROR(dindU.transfer_from(hindU));
CHECK_HIP_ERROR(dvalU.transfer_from(hvalU));
CHECK_HIP_ERROR(dpivP.transfer_from(hpivP));
CHECK_HIP_ERROR(dpivQ.transfer_from(hpivQ));
CHECK_HIP_ERROR(dB.transfer_from(hB));
}
}
template <typename T, typename Td, typename Ud, typename Th, typename Uh>
void csrrf_solve_getError(hipsolverRfHandle_t handle,
const int n,
const int nrhs,
const int nnzA,
Ud& dptrA,
Ud& dindA,
Td& dvalA,
const int nnzL,
Ud& dptrL,
Ud& dindL,
Td& dvalL,
const int nnzU,
Ud& dptrU,
Ud& dindU,
Td& dvalU,
Ud& dpivP,
Ud& dpivQ,
Td& dB,
const int ldb,
Td& dWork,
Uh& hptrA,
Uh& hindA,
Th& hvalA,
Uh& hptrL,
Uh& hindL,
Th& hvalL,
Uh& hptrU,
Uh& hindU,
Th& hvalU,
Uh& hpivP,
Uh& hpivQ,
Th& hB,
Th& hX,
Th& hXres,
double* max_err,
const fs::path testcase)
{
// input data initialization
csrrf_solve_initData<true, true, T>(handle,
n,
nrhs,
nnzA,
dptrA,
dindA,
dvalA,
nnzL,
dptrL,
dindL,
dvalL,
nnzU,
dptrU,
dindU,
dvalU,
dpivP,
dpivQ,
dB,
ldb,
hptrA,
hindA,
hvalA,
hptrL,
hindL,
hvalL,
hptrU,
hindU,
hvalU,
hpivP,
hpivQ,
hB,
hX,
testcase);
// execute computations
// GPU lapack
CHECK_ROCBLAS_ERROR(hipsolverRfSetupDevice(n,
nnzA,
dptrA.data(),
dindA.data(),
dvalA.data(),
nnzL,
dptrL.data(),
dindL.data(),
dvalL.data(),
nnzU,
dptrU.data(),
dindU.data(),
dvalU.data(),
dpivP.data(),
dpivQ.data(),
handle));
CHECK_ROCBLAS_ERROR(hipsolverRfAnalyze(handle));
CHECK_ROCBLAS_ERROR(hipsolverRfResetValues(
n, nnzA, dptrA.data(), dindA.data(), dvalA.data(), dpivP.data(), dpivQ.data(), handle));
CHECK_ROCBLAS_ERROR(hipsolverRfRefactor(handle));
CHECK_ROCBLAS_ERROR(
hipsolverRfSolve(handle, dpivP, dpivQ, nrhs, dWork.data(), n, dB.data(), ldb));
CHECK_HIP_ERROR(hXres.transfer_from(dB));
// compare computed results with original result
*max_err = norm_error('I', n, nrhs, ldb, hX[0], hXres[0]);
}
template <typename T, typename Td, typename Ud, typename Th, typename Uh>
void csrrf_solve_getPerfData(hipsolverRfHandle_t handle,
const int n,
const int nrhs,
const int nnzA,
Ud& dptrA,
Ud& dindA,
Td& dvalA,
const int nnzL,
Ud& dptrL,
Ud& dindL,
Td& dvalL,
const int nnzU,
Ud& dptrU,
Ud& dindU,
Td& dvalU,
Ud& dpivP,
Ud& dpivQ,
Td& dB,
const int ldb,
Td& dWork,
Uh& hptrA,
Uh& hindA,
Th& hvalA,
Uh& hptrL,
Uh& hindL,
Th& hvalL,
Uh& hptrU,
Uh& hindU,
Th& hvalU,
Uh& hpivP,
Uh& hpivQ,
Th& hB,
Th& hX,
double* gpu_time_used,
double* cpu_time_used,
const int hot_calls,
const bool perf,
const fs::path testcase)
{
*cpu_time_used = nan(""); // no timing on cpu-lapack execution
*gpu_time_used = nan(""); // no timing on gpu-lapack execution
}
template <typename T>
void testing_csrrf_solve(Arguments& argus)
{
// get arguments
hipsolverRf_local_handle handle;
int n = argus.get<int>("n");
int nrhs = argus.get<int>("nrhs", n);
int nnzA = argus.get<int>("nnzA");
int ldb = argus.get<int>("ldb", n);
int hot_calls = argus.iters;
// check non-supported values
// N/A
// check invalid sizes
bool invalid_size = (n < 0 || nrhs < 0 || nnzA < 0 || ldb < n);
if(invalid_size)
{
// EXPECT_ROCBLAS_STATUS(rocsolver_csrrf_solve(handle, n, nrhs, nnzA, (int*)nullptr,
// (int*)nullptr, (T*)nullptr,
// (int*)nullptr, (int*)nullptr,
// rfinfo, (T*)nullptr, ldb),
// rocblas_status_invalid_size);
if(argus.timing)
rocsolver_bench_inform(inform_invalid_size);
return;
}
// determine existing test case
if(n > 0)
{
if(n <= 35)
n = 20;
else if(n <= 75)
n = 50;
else if(n <= 175)
n = 100;
else
n = 250;
}
if(n <= 50) // small case
{
if(nnzA <= 80)
nnzA = 60;
else if(nnzA <= 120)
nnzA = 100;
else
nnzA = 140;
}
else // large case
{
if(nnzA <= 400)
nnzA = 300;
else if(nnzA <= 600)
nnzA = 500;
else
nnzA = 700;
}
// read/set corresponding nnzL and nnzU
int nnzL, nnzU;
fs::path testcase;
if(n > 0)
{
fs::path file;
std::string folder = std::string("mat_") + std::to_string(n) + "_" + std::to_string(nnzA);
testcase = get_sparse_data_dir() / folder;
file = testcase / "ptrA";
read_last(file.string(), &nnzA);
file = testcase / "ptrL";
read_last(file.string(), &nnzL);
file = testcase / "ptrU";
read_last(file.string(), &nnzU);
}
// determine existing right-hand-side
if(nrhs > 0)
{
nrhs = 1;
}
// determine sizes
size_t size_ptrA = size_t(n) + 1;
size_t size_indA = size_t(nnzA);
size_t size_valA = size_t(nnzA);
size_t size_ptrL = size_t(n) + 1;
size_t size_indL = size_t(nnzL);
size_t size_valL = size_t(nnzL);
size_t size_ptrU = size_t(n) + 1;
size_t size_indU = size_t(nnzU);
size_t size_valU = size_t(nnzU);
size_t size_pivP = size_t(n);
size_t size_pivQ = size_t(n);
size_t size_BX = size_t(ldb) * nrhs;
size_t size_BXres = 0;
if(argus.unit_check || argus.norm_check)
size_BXres = size_BX;
double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;
// memory allocations
host_strided_batch_vector<int> hptrA(size_ptrA, 1, size_ptrA, 1);
host_strided_batch_vector<int> hindA(size_indA, 1, size_indA, 1);
host_strided_batch_vector<T> hvalA(size_valA, 1, size_valA, 1);
host_strided_batch_vector<int> hptrL(size_ptrL, 1, size_ptrL, 1);
host_strided_batch_vector<int> hindL(size_indL, 1, size_indL, 1);
host_strided_batch_vector<T> hvalL(size_valL, 1, size_valL, 1);
host_strided_batch_vector<int> hptrU(size_ptrU, 1, size_ptrU, 1);
host_strided_batch_vector<int> hindU(size_indU, 1, size_indU, 1);
host_strided_batch_vector<T> hvalU(size_valU, 1, size_valU, 1);
host_strided_batch_vector<int> hpivP(size_pivP, 1, size_pivP, 1);
host_strided_batch_vector<int> hpivQ(size_pivQ, 1, size_pivQ, 1);
host_strided_batch_vector<T> hB(size_BX, 1, size_BX, 1);
host_strided_batch_vector<T> hX(size_BX, 1, size_BX, 1);
host_strided_batch_vector<T> hXres(size_BXres, 1, size_BXres, 1);
device_strided_batch_vector<int> dptrA(size_ptrA, 1, size_ptrA, 1);
device_strided_batch_vector<int> dindA(size_indA, 1, size_indA, 1);
device_strided_batch_vector<T> dvalA(size_valA, 1, size_valA, 1);
device_strided_batch_vector<int> dptrL(size_ptrL, 1, size_ptrL, 1);
device_strided_batch_vector<int> dindL(size_indL, 1, size_indL, 1);
device_strided_batch_vector<T> dvalL(size_valL, 1, size_valL, 1);
device_strided_batch_vector<int> dptrU(size_ptrU, 1, size_ptrU, 1);
device_strided_batch_vector<int> dindU(size_indU, 1, size_indU, 1);
device_strided_batch_vector<T> dvalU(size_valU, 1, size_valU, 1);
device_strided_batch_vector<int> dpivP(size_pivP, 1, size_pivP, 1);
device_strided_batch_vector<int> dpivQ(size_pivQ, 1, size_pivQ, 1);
device_strided_batch_vector<T> dB(size_BX, 1, size_BX, 1);
CHECK_HIP_ERROR(dptrA.memcheck());
CHECK_HIP_ERROR(dptrL.memcheck());
CHECK_HIP_ERROR(dptrU.memcheck());
if(size_indA)
CHECK_HIP_ERROR(dindA.memcheck());
if(size_valA)
CHECK_HIP_ERROR(dvalA.memcheck());
if(size_indL)
CHECK_HIP_ERROR(dindL.memcheck());
if(size_valL)
CHECK_HIP_ERROR(dvalL.memcheck());
if(size_indU)
CHECK_HIP_ERROR(dindU.memcheck());
if(size_valU)
CHECK_HIP_ERROR(dvalU.memcheck());
if(size_pivP)
CHECK_HIP_ERROR(dpivP.memcheck());
if(size_pivQ)
CHECK_HIP_ERROR(dpivQ.memcheck());
if(size_BX)
CHECK_HIP_ERROR(dB.memcheck());
int size_W = n * nrhs;
device_strided_batch_vector<T> dWork(size_W, 1, size_W, 1);
if(size_W)
CHECK_HIP_ERROR(dWork.memcheck());
// check computations
if(argus.unit_check || argus.norm_check)
csrrf_solve_getError<T>(handle,
n,
nrhs,
nnzA,
dptrA,
dindA,
dvalA,
nnzL,
dptrL,
dindL,
dvalL,
nnzU,
dptrU,
dindU,
dvalU,
dpivP,
dpivQ,
dB,
ldb,
dWork,
hptrA,
hindA,
hvalA,
hptrL,
hindL,
hvalL,
hptrU,
hindU,
hvalU,
hpivP,
hpivQ,
hB,
hX,
hXres,
&max_error,
testcase);
// collect performance data
if(argus.timing)
csrrf_solve_getPerfData<T>(handle,
n,
nrhs,
nnzA,
dptrA,
dindA,
dvalA,
nnzL,
dptrL,
dindL,
dvalL,
nnzU,
dptrU,
dindU,
dvalU,
dpivP,
dpivQ,
dB,
ldb,
dWork,
hptrA,
hindA,
hvalA,
hptrL,
hindL,
hvalL,
hptrU,
hindU,
hvalU,
hpivP,
hpivQ,
hB,
hX,
&gpu_time_used,
&cpu_time_used,
hot_calls,
argus.perf,
testcase);
// validate results for rocsolver-test
// using n * machine_precision as tolerance
if(argus.unit_check)
ROCSOLVER_TEST_CHECK(T, max_error, n);
// output results for rocsolver-bench
if(argus.timing)
{
if(!argus.perf)
{
std::cerr << "\n============================================\n";
std::cerr << "Arguments:\n";
std::cerr << "============================================\n";
rocsolver_bench_output("n", "nrhs", "nnzA", "ldb");
rocsolver_bench_output(n, nrhs, nnzA, ldb);
std::cerr << "\n============================================\n";
std::cerr << "Results:\n";
std::cerr << "============================================\n";
if(argus.norm_check)
{
rocsolver_bench_output("cpu_time_us", "gpu_time_us", "error");
rocsolver_bench_output(cpu_time_used, gpu_time_used, max_error);
}
else
{
rocsolver_bench_output("cpu_time_us", "gpu_time_us");
rocsolver_bench_output(cpu_time_used, gpu_time_used);
}
std::cerr << std::endl;
}
else
{
if(argus.norm_check)
rocsolver_bench_output(gpu_time_used, max_error);
else
rocsolver_bench_output(gpu_time_used);
}
}
// ensure all arguments were consumed
argus.validate_consumed();
}
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