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TheRock/rocm-libraries/projects/hipsparselt/clients/include/utility.hpp
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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

690 lines
24 KiB
C++

/*******************************************************************************
*
* MIT License
*
* Copyright (c) 2022-2026 Advanced Micro Devices, Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*
*******************************************************************************/
#pragma once
#include "hipsparselt_vector.hpp"
#include <cstdio>
#include <hipsparselt/hipsparselt.h>
#include <iomanip>
#include <iostream>
#include <string>
#include <type_traits>
#include <vector>
#include <stdlib.h>
/*!\file
* \brief provide common utilities
*/
// We use hipsparselt_cout and hipsparselt_cerr instead of std::cout, std::cerr, stdout and stderr,
// for thread-safe IO.
//
// All stdio and std::ostream functions related to stdout and stderr are poisoned, as are
// functions which can create buffer overflows, or which are inherently thread-unsafe.
//
// This must come after the header #includes above, to avoid poisoning system headers.
//
// This is only enabled for hipsparselt-test and hipsparselt-bench.
//
// If you are here because of a poisoned identifier error, here is the rationale for each
// included identifier:
//
// cout, stdout: hipsparselt_cout should be used instead, for thread-safe and atomic line buffering
// cerr, stderr: hipsparselt_cerr should be used instead, for thread-safe and atomic line buffering
// clog: C++ stream which should not be used
// gets: Always unsafe; buffer-overflows; removed from later versions of the language; use fgets
// puts, putchar, fputs, printf, fprintf, vprintf, vfprintf: Use hipsparselt_cout or hipsparselt_cerr
// sprintf, vsprintf: Possible buffer overflows; us snprintf or vsnprintf instead
// strerror: Thread-unsafe; use snprintf / dprintf with %m or strerror_* alternatives
// strsignal: Thread-unsafe; use sys_siglist[signal] instead
// strtok: Thread-unsafe; use strtok_r
// gmtime, ctime, asctime, localtime: Thread-unsafe
// tmpnam: Thread-unsafe; use mkstemp or related functions instead
// putenv: Use setenv instead
// clearenv, fcloseall, ecvt, fcvt: Miscellaneous thread-unsafe functions
// sleep: Might interact with signals by using alarm(); use nanosleep() instead
// abort: Does not abort as cleanly as hipsparselt_abort, and can be caught by a signal handler
#if defined(GOOGLE_TEST) || defined(HIPSPARSELT_BENCH)
#undef stdout
#undef stderr
#pragma GCC poison cout cerr clog stdout stderr gets puts putchar fputs fprintf printf sprintf \
vfprintf vprintf vsprintf perror strerror strtok gmtime ctime asctime localtime tmpnam putenv \
clearenv fcloseall ecvt fcvt sleep abort strsignal
#else
// Suppress warnings about hipMalloc(), hipFree() except in hipsparselt-test and hipsparselt-bench
#undef hipMalloc
#undef hipFree
#endif
#define LIMITED_MEMORY_STRING "Error: Attempting to allocate more memory than available."
#define TOO_MANY_DEVICES_STRING "Error: Too many devices requested."
#define HMM_NOT_SUPPORTED "Error: HMM not supported."
// TODO: This is dependent on internal gtest behaviour.
// Compared with result.message() when a test ended. Note that "Succeeded\n" is
// added to the beginning of the message automatically by gtest, so this must be compared.
#define LIMITED_MEMORY_STRING_GTEST "Succeeded\n" LIMITED_MEMORY_STRING
#define TOO_MANY_DEVICES_STRING_GTEST "Succeeded\n" TOO_MANY_DEVICES_STRING
#define HMM_NOT_SUPPORTED_GTEST "Succeeded\n" HMM_NOT_SUPPORTED
enum class hipsparselt_batch_type
{
none = 0,
batched,
strided_batched
};
/* ============================================================================================ */
/*! \brief local handle which is automatically created and destroyed */
class hipsparselt_local_handle
{
hipsparseLtHandle_t m_handle;
void* m_memory = nullptr;
public:
hipsparselt_local_handle();
explicit hipsparselt_local_handle(const Arguments& arg);
~hipsparselt_local_handle();
hipsparselt_local_handle(const hipsparselt_local_handle&) = delete;
hipsparselt_local_handle(hipsparselt_local_handle&&) = delete;
hipsparselt_local_handle& operator=(const hipsparselt_local_handle&) = delete;
hipsparselt_local_handle& operator=(hipsparselt_local_handle&&) = delete;
// Allow hipsparselt_local_handle to be used anywhere hipsparseLtHandle_t is expected
operator hipsparseLtHandle_t&()
{
return m_handle;
}
operator const hipsparseLtHandle_t&() const
{
return m_handle;
}
operator hipsparseLtHandle_t*()
{
return &m_handle;
}
operator const hipsparseLtHandle_t*() const
{
return &m_handle;
}
};
typedef enum hipsparselt_matrix_type_
{
hipsparselt_matrix_type_dense = 1, /**< dense matrix type. */
hipsparselt_matrix_type_structured = 2, /**< structured matrix type. */
} hipsparselt_matrix_type;
/* ============================================================================================ */
/*! \brief local matrix descriptor which is automatically created and destroyed */
class hipsparselt_local_mat_descr
{
hipsparseLtMatDescriptor_t m_descr;
hipsparseStatus_t m_status = HIPSPARSE_STATUS_NOT_INITIALIZED;
static constexpr int alignment = 16;
public:
hipsparselt_local_mat_descr(hipsparselt_matrix_type mtype,
const hipsparseLtHandle_t* handle,
int64_t row,
int64_t col,
int64_t ld,
hipDataType type,
hipsparseOrder_t order)
{
if(mtype == hipsparselt_matrix_type_structured)
this->m_status = hipsparseLtStructuredDescriptorInit(handle,
&this->m_descr,
row,
col,
ld,
this->alignment,
type,
order,
HIPSPARSELT_SPARSITY_50_PERCENT);
else
this->m_status = hipsparseLtDenseDescriptorInit(
handle, &this->m_descr, row, col, ld, this->alignment, type, order);
}
~hipsparselt_local_mat_descr()
{
if(this->m_status == HIPSPARSE_STATUS_SUCCESS)
hipsparseLtMatDescriptorDestroy(&this->m_descr);
}
hipsparselt_local_mat_descr(const hipsparselt_local_mat_descr&) = delete;
hipsparselt_local_mat_descr(hipsparselt_local_mat_descr&&) = delete;
hipsparselt_local_mat_descr& operator=(const hipsparselt_local_mat_descr&) = delete;
hipsparselt_local_mat_descr& operator=(hipsparselt_local_mat_descr&&) = delete;
hipsparseStatus_t status()
{
return m_status;
}
// Allow hipsparselt_local_mat_descr to be used anywhere hipsparseLtMatDescriptor_t is expected
operator hipsparseLtMatDescriptor_t&()
{
return m_descr;
}
operator const hipsparseLtMatDescriptor_t&() const
{
return m_descr;
}
operator hipsparseLtMatDescriptor_t*()
{
return &m_descr;
}
operator const hipsparseLtMatDescriptor_t*() const
{
return &m_descr;
}
};
/* ============================================================================================ */
/*! \brief local matrix multiplication descriptor which is automatically created and destroyed */
class hipsparselt_local_matmul_descr
{
hipsparseLtMatmulDescriptor_t m_descr;
hipsparseStatus_t m_status = HIPSPARSE_STATUS_NOT_INITIALIZED;
public:
hipsparselt_local_matmul_descr(const hipsparseLtHandle_t* handle,
hipsparseOperation_t opA,
hipsparseOperation_t opB,
const hipsparseLtMatDescriptor_t* matA,
const hipsparseLtMatDescriptor_t* matB,
const hipsparseLtMatDescriptor_t* matC,
const hipsparseLtMatDescriptor_t* matD,
hipsparseLtComputetype_t compute_type)
{
this->m_status = hipsparseLtMatmulDescriptorInit(
handle, &this->m_descr, opA, opB, matA, matB, matC, matD, compute_type);
}
~hipsparselt_local_matmul_descr() {}
hipsparselt_local_matmul_descr(const hipsparselt_local_matmul_descr&) = delete;
hipsparselt_local_matmul_descr(hipsparselt_local_matmul_descr&&) = delete;
hipsparselt_local_matmul_descr& operator=(const hipsparselt_local_matmul_descr&) = delete;
hipsparselt_local_matmul_descr& operator=(hipsparselt_local_matmul_descr&&) = delete;
hipsparseStatus_t status()
{
return m_status;
}
// Allow hipsparselt_local_matmul_descr to be used anywhere hipsparseLtMatmulDescriptor_t is expected
operator hipsparseLtMatmulDescriptor_t&()
{
return m_descr;
}
operator const hipsparseLtMatmulDescriptor_t&() const
{
return m_descr;
}
operator hipsparseLtMatmulDescriptor_t*()
{
return &m_descr;
}
operator const hipsparseLtMatmulDescriptor_t*() const
{
return &m_descr;
}
};
/* ================================================================================================================= */
/*! \brief local matrix multiplication algorithm selection descriptor which is automatically created and destroyed */
class hipsparselt_local_matmul_alg_selection
{
hipsparseLtMatmulAlgSelection_t m_alg_sel;
hipsparseStatus_t m_status = HIPSPARSE_STATUS_NOT_INITIALIZED;
public:
hipsparselt_local_matmul_alg_selection(const hipsparseLtHandle_t* handle,
const hipsparseLtMatmulDescriptor_t* matmul,
hipsparseLtMatmulAlg_t alg)
{
this->m_status = hipsparseLtMatmulAlgSelectionInit(handle, &this->m_alg_sel, matmul, alg);
}
~hipsparselt_local_matmul_alg_selection()
{
if(this->m_status == HIPSPARSE_STATUS_SUCCESS)
hipsparseLtMatmulAlgSelectionDestroy(&this->m_alg_sel);
}
hipsparselt_local_matmul_alg_selection(const hipsparselt_local_matmul_alg_selection&) = delete;
hipsparselt_local_matmul_alg_selection(hipsparselt_local_matmul_alg_selection&&) = delete;
hipsparselt_local_matmul_alg_selection& operator=(const hipsparselt_local_matmul_alg_selection&)
= delete;
hipsparselt_local_matmul_alg_selection& operator=(hipsparselt_local_matmul_alg_selection&&)
= delete;
hipsparseStatus_t status()
{
return m_status;
}
operator hipsparseLtMatmulAlgSelection_t&()
{
return m_alg_sel;
}
operator const hipsparseLtMatmulAlgSelection_t&() const
{
return m_alg_sel;
}
operator hipsparseLtMatmulAlgSelection_t*()
{
return &m_alg_sel;
}
operator const hipsparseLtMatmulAlgSelection_t*() const
{
return &m_alg_sel;
}
};
/* ================================================================================================================= */
/*! \brief local matrix multiplication plan descriptor which is automatically created and destroyed */
class hipsparselt_local_matmul_plan
{
hipsparseLtMatmulPlan_t m_plan;
hipsparseStatus_t m_status = HIPSPARSE_STATUS_NOT_INITIALIZED;
public:
hipsparselt_local_matmul_plan(const hipsparseLtHandle_t* handle,
const hipsparseLtMatmulDescriptor_t* matmul,
const hipsparseLtMatmulAlgSelection_t* alg_sel)
{
this->m_status = hipsparseLtMatmulPlanInit(handle, &this->m_plan, matmul, alg_sel);
}
~hipsparselt_local_matmul_plan()
{
if(this->m_status == HIPSPARSE_STATUS_SUCCESS)
hipsparseLtMatmulPlanDestroy(&this->m_plan);
}
hipsparselt_local_matmul_plan(const hipsparselt_local_matmul_plan&) = delete;
hipsparselt_local_matmul_plan(hipsparselt_local_matmul_plan&&) = delete;
hipsparselt_local_matmul_plan& operator=(const hipsparselt_local_matmul_plan&) = delete;
hipsparselt_local_matmul_plan& operator=(hipsparselt_local_matmul_plan&&) = delete;
hipsparseStatus_t status()
{
return this->m_status;
}
operator hipsparseLtMatmulPlan_t&()
{
return m_plan;
}
operator const hipsparseLtMatmulPlan_t&() const
{
return m_plan;
}
operator hipsparseLtMatmulPlan_t*()
{
return &m_plan;
}
operator const hipsparseLtMatmulPlan_t*() const
{
return &m_plan;
}
};
/* ============================================================================================ */
/* device query and print out their ID and name */
int64_t query_device_property();
/* set current device to device_id */
void set_device(int64_t device_id);
/* ============================================================================================ */
/* timing: HIP only provides very limited timers function clock() and not general;
hipsparselt sync CPU and device and use more accurate CPU timer*/
/*! \brief CPU Timer(in microsecond): synchronize with the default device and return wall time */
double get_time_us_sync_device();
/*! \brief CPU Timer(in microsecond): synchronize with given queue/stream and return wall time */
double get_time_us_sync(hipStream_t stream);
/*! \brief CPU Timer(in microsecond): no GPU synchronization and return wall time */
double get_time_us_no_sync();
/* ============================================================================================ */
// Return path of this executable
std::string hipsparselt_exepath();
/* ============================================================================================ */
// Temp directory rooted random path
std::string hipsparselt_tempname();
/* ============================================================================================ */
/* Read environment variable */
const char* read_env_var(const char* env_var);
/* ============================================================================================ */
/* Compute strided batched matrix allocation size allowing for strides smaller than full matrix */
size_t strided_batched_matrix_size(int rows, int cols, int lda, int64_t stride, int batch_count);
/* ============================================================================================ */
/*! \brief Debugging purpose, print out CPU and GPU result matrix, not valid in complex number */
template <typename T>
inline void hipsparselt_print_matrix(
std::vector<T> CPU_result, std::vector<T> GPU_result, size_t m, size_t n, size_t lda)
{
for(size_t i = 0; i < m; i++)
for(size_t j = 0; j < n; j++)
{
hipsparselt_cout << "matrix col " << i << ", row " << j
<< ", CPU result=" << CPU_result[j + i * lda]
<< ", GPU result=" << GPU_result[j + i * lda] << "\n";
}
}
template <typename T>
void hipsparselt_print_matrix(const char* name, T* A, size_t m, size_t n, size_t lda)
{
hipsparselt_cout << "---------- " << name << " ----------\n";
for(size_t i = 0; i < m; i++)
{
for(size_t j = 0; j < n; j++)
hipsparselt_cout << std::setprecision(0) << std::setw(5) << A[i + j * lda] << " ";
hipsparselt_cout << std::endl;
}
}
/* ============================================================================= */
/*! \brief For testing purposes, to convert a regular matrix to a banded matrix. */
template <typename T>
inline void regular_to_banded(
bool upper, const T* A, int64_t lda, T* AB, int64_t ldab, int64_t n, int64_t k)
{
// convert regular hA matrix to banded hAB matrix
for(int j = 0; j < n; j++)
{
int64_t min1 = upper ? std::max(0, static_cast<int>(j - k)) : j;
int64_t max1 = upper ? j : std::min(static_cast<int>(n - 1), static_cast<int>(j + k));
int64_t m = upper ? k - j : -j;
// Move bands of hA into new banded hAB format.
for(int i = min1; i <= max1; i++)
AB[j * ldab + (m + i)] = A[j * lda + i];
min1 = upper ? k + 1 : std::min(k + 1, n - j);
max1 = ldab - 1;
// fill in bottom with random data to ensure we aren't using it.
// for !upper, fill in bottom right triangle as well.
for(int i = min1; i <= max1; i++)
hipsparselt_init<T>(AB + j * ldab + i, 1, 1, 1);
// for upper, fill in top left triangle with random data to ensure
// we aren't using it.
if(upper)
{
for(int i = 0; i < m; i++)
hipsparselt_init<T>(AB + j * ldab + i, 1, 1, 1);
}
}
}
/* =============================================================================== */
/*! \brief For testing purposes, zeros out elements not needed in a banded matrix. */
template <typename T>
inline void banded_matrix_setup(bool upper, T* A, int64_t lda, int64_t n, int64_t k)
{
// Made A a banded matrix with k sub/super-diagonals
for(int i = 0; i < n; i++)
{
for(int j = 0; j < n; j++)
{
if(upper && (j > k + i || i > j))
A[j * n + i] = T(0);
else if(!upper && (i > k + j || j > i))
A[j * n + i] = T(0);
}
}
}
/* ============================================================================================= */
/*! \brief For testing purposes, to convert a regular matrix to a packed matrix. */
template <typename T>
inline void regular_to_packed(bool upper, const T* A, T* AP, int64_t n)
{
int index = 0;
if(upper)
{
for(int i = 0; i < n; i++)
{
for(int j = 0; j <= i; j++)
{
AP[index++] = A[j + i * n];
}
}
}
else
{
for(int i = 0; i < n; i++)
{
for(int j = i; j < n; j++)
{
AP[index++] = A[j + i * n];
}
}
}
}
template <typename T>
void print_strided_batched(
const char* name, T* A, int64_t n1, int64_t n2, int64_t n3, int64_t s1, int64_t s2, int64_t s3)
{
constexpr bool is_int = std::is_same<T, int8_t>();
using Tp = std::conditional_t<is_int, int32_t, float>;
// n1, n2, n3 are matrix dimensions, sometimes called m, n, batch_count
// s1, s1, s3 are matrix strides, sometimes called 1, lda, stride_a
hipsparselt_cout << "---------- " << name << " ----------\n";
int max_size = 128;
for(int i3 = 0; i3 < n3 && i3 < max_size; i3++)
{
for(int i1 = 0; i1 < n1 && i1 < max_size; i1++)
{
for(int i2 = 0; i2 < n2 && i2 < max_size; i2++)
{
hipsparselt_cout << static_cast<Tp>(A[(i1 * s1) + (i2 * s2) + (i3 * s3)]) << "|";
}
hipsparselt_cout << "\n";
}
if(i3 < (n3 - 1) && i3 < (max_size - 1))
hipsparselt_cout << "\n";
}
hipsparselt_cout << std::flush;
}
inline hipsparseStatus_t expected_hipsparse_status_of_matrix_size(hipDataType type,
int64_t m,
int64_t n,
int64_t ld,
hipsparseOrder_t order,
bool isSparse = false)
{
int row_ = 8;
int col_ = 8;
int ld_ = -1;
int bytes = 1;
#ifdef __HIP_PLATFORM_NVIDIA__
switch(type)
{
case HIP_R_8I:
#if HIP_FP8_TYPE_OCP
case HIP_R_8F_E4M3:
case HIP_R_8F_E5M2:
#endif
#if HIP_FP8_TYPE_FNUZ
case HIP_R_8F_E4M3_FNUZ:
case HIP_R_8F_E5M2_FNUZ:
#endif
if(isSparse)
row_ = col_ = ld_ = 32;
else
row_ = col_ = ld_ = 16;
break;
case HIP_R_16BF:
case HIP_R_16F:
bytes = 2;
if(isSparse)
row_ = col_ = ld_ = 16;
else
ld_ = 8;
break;
default:
break;
}
#else
switch(type)
{
case HIP_R_8I:
#if HIP_FP8_TYPE_OCP
case HIP_R_8F_E4M3:
case HIP_R_8F_E5M2:
#endif
#if HIP_FP8_TYPE_FNUZ
case HIP_R_8F_E4M3_FNUZ:
case HIP_R_8F_E5M2_FNUZ:
#endif
row_ = col_ = 16;
break;
case HIP_R_16BF:
case HIP_R_16F:
bytes = 2;
break;
default:
break;
}
#endif
if(m <= 0 || n <= 0)
return HIPSPARSE_STATUS_INVALID_VALUE;
#ifdef __HIP_PLATFORM_AMD__
if(m < row_ || n < col_)
return HIPSPARSE_STATUS_NOT_SUPPORTED;
if(m % row_ != 0 || n % col_ != 0)
return HIPSPARSE_STATUS_NOT_SUPPORTED;
#endif
{
if(order == HIPSPARSE_ORDER_COL)
{
if(m > ld)
return HIPSPARSE_STATUS_INVALID_VALUE;
if(ld_ != -1 && ld % ld_ != 0)
return HIPSPARSE_STATUS_NOT_SUPPORTED;
#ifdef __HIP_PLATFORM_NVIDIA__
if(n * ld * bytes > 4294967295)
return HIPSPARSE_STATUS_INVALID_VALUE;
#endif
}
else
{
if(n > ld)
return HIPSPARSE_STATUS_INVALID_VALUE;
if(ld_ != -1 && ld % ld_ != 0)
return HIPSPARSE_STATUS_NOT_SUPPORTED;
#ifdef __HIP_PLATFORM_NVIDIA__
if(m * ld * bytes > 4294967295)
return HIPSPARSE_STATUS_INVALID_VALUE;
#endif
}
}
#ifdef __HIP_PLATFORM_NVIDIA__
if(m < row_ || n < col_)
return HIPSPARSE_STATUS_NOT_SUPPORTED;
if(m % row_ != 0 || n % col_ != 0)
return HIPSPARSE_STATUS_NOT_SUPPORTED;
#endif
return HIPSPARSE_STATUS_SUCCESS;
}
inline hipsparseStatus_t expected_hipsparse_status_of_matrix_stride(
int64_t stride, int64_t m, int64_t n, int64_t ld, hipsparseOrder_t order)
{
if(stride == 0 || stride >= (order == HIPSPARSE_ORDER_COL ? ld * n : ld * m))
return HIPSPARSE_STATUS_SUCCESS;
else
return HIPSPARSE_STATUS_INVALID_VALUE;
}
class Logger
{
public:
Logger(int log_level)
{
this->log_level = log_level;
this->pre_log_level = -1;
if(this->log_level)
{
char* str_layer_mode;
if((str_layer_mode = getenv("HIPSPARSELT_LOG_LEVEL")) != NULL)
{
this->pre_log_level = atoi(str_layer_mode);
}
setenv("HIPSPARSELT_LOG_LEVEL", std::to_string(this->log_level).c_str(), 1);
}
}
~Logger()
{
if(this->log_level)
{
if(this->pre_log_level == -1)
unsetenv("HIPSPARSELT_LOG_LEVEL");
else
setenv("HIPSPARSELT_LOG_LEVEL", std::to_string(this->pre_log_level).c_str(), 1);
}
}
int log_level;
int pre_log_level;
};