Design Documentation#
Design and Philosophy#
The rocSPARSE library is developed using the Hourglass API approach. This is especially helpful to offer a thin C89 API to the user and still get all the convenience of C++. As a side effect, ABI related binary compatibility issues can be avoided. Furthermore, this approach allows rocSPARSE routines to be used by other programming languages.
In public API header files, rocSPARSE only relies on functions, pointers, forward declared structs, enumerations and type defs. Additionally, rocSPARSE introduces multiple library and object handles by using opaque types to hide layout and implementation details from the user.
Temporary Device Memory#
Many routines exposed by the rocSPARSE API require a temporary storage buffer on the device.
rocSPARSE notion is that the user is responsible for such buffer allocation and deallocation.
Hence, allocated buffers can be re-used and do not need to be regularly (de)allocated on every single API call.
For this purpose, routines that require a temporary storage buffer offer a special API function to query for the storage buffer size, e.g. rocsparse_scsrsv_buffer_size().
Contributing#
How to contribute#
Our code contriubtion guidelines closely follows the model of GitHub pull-requests. This repository follows the git flow workflow, which dictates a /master branch where releases are cut, and a /develop branch which serves as an integration branch for new code.
A git extention has been developed to ease the use of the ‘git flow’ methodology, but requires manual installation by the user. Please refer to the projects wiki.
Pull-request guidelines#
Target the develop branch for integration.
Ensure code builds successfully.
Do not break existing test cases
New functionality will only be merged with new unit tests.
New unit tests should integrate within the existing googletest framework.
Tests must have good code coverage.
Code must also have benchmark tests, and performance must approach the compute bound limit or memory bound limit.
StyleGuide#
Interface
All public APIs are C89 compatible; all other library code should use C++14.
Our minimum supported compiler is clang 3.6.
Avoid CamelCase.
This rule applies specifically to publicly visible APIs, but is also encouraged (not mandated) for internal code.
Format
C and C++ code is formatted using clang-format. To format a file, use
/opt/rocm/llvm/bin/clang-format -style=file -i <file>
To format all files, run the following script in rocSPARSE directory:
#!/bin/bash
find . -iname '*.h' \
-o -iname '*.hpp' \
-o -iname '*.cpp' \
-o -iname '*.h.in' \
-o -iname '*.hpp.in' \
-o -iname '*.cpp.in' \
-o -iname '*.cl' \
| grep -v 'build' \
| xargs -n 1 -P 8 -I{} /opt/rocm/llvm/bin/clang-format -style=file -i {}
Library Source Organization#
The library/include directory#
This directory contains all files that are exposed to the user. The rocSPARSE API, is declared here.
File |
Description |
|---|---|
rocsparse.h |
Includes all other API related rocSPARSE header files. |
rocsparse-auxiliary.h |
Declares all rocSPARSE auxiliary functions, such as handle and descriptor management. |
rocsparse-complex-types.h |
Defines the rocSPARSE complex data types rocsparse_float_complex and rocsparse_double_complex. |
rocsparse-functions.h |
Declares all rocSPARSE Sparse Linear Algebra Subroutines of Level1, 2, 3, Extra, Preconditioner, Format Conversion, Reordering, and Utility. |
rocsparse-types.h |
Defines all data types used by rocSPARSE. |
rocsparse-version.h.in |
Provides the configured version and settings that is initially set by CMake during compilation. |
The library/src/ directory#
This directory contains all rocSPARSE library source files. The root of the library/src/ directory hosts the implementation of the library handle and auxiliary functions. Furthermore, each sub-directory is responsible for the specific class of sparse linear algebra subroutines. Finally, the library/src/include directory defines Commonly Shared Device-Code, Status-Flag Macros, The rocsparse_mat_info Structure and Logging.
File |
Description |
|---|---|
handle.cpp |
Implementation of opaque handle structures. |
rocsparse_auxiliary.cpp |
Implementation of auxiliary functions, e.g. create and destroy handles. |
status.cpp |
Implementation of |
include/common.h |
Commonly used functions among several rocSPARSE routines, see Commonly Shared Device-Code. |
include/definitions.h |
Status-flag macros are defined here, see Status-Flag Macros. |
include/handle.h |
Declaration of opaque handle structures. |
include/logging.h |
Implementation of different rocSPARSE logging helper functions. |
include/status.h |
Declaration of |
include/utility.h |
Implementation of different rocSPARSE logging functionality. |
The clients/ directory#
This directory contains all clients, e.g. samples, unit tests and benchmarks. Further details are given in Clients.
Sparse Linear Algebra Subroutines#
Each sparse linear algebra subroutine is implemented in a set of source files in the corresponding directory: rocsparse_subroutine.cpp, rocsparse_subroutine.hpp and subroutine_device.h.
rocsparse_subroutine.cpp implements the C wrapper and the API functionality for each precision supported.
Furthermore, rocsparse_subroutine.hpp implements the API functionality, using the precision as template parameter.
Finally, subroutine_device.h implements the device code, required for the computation of the subroutine.
Note
Each API exposed subroutine is expected to return a rocsparse_status.
Note
Additionally, each device function is expected to use the user given stream which is accessible through the libraries handle.
Below is a sample for rocsparse_subroutine.cpp, rocsparse_subroutine.hpp and subroutine_device.h.
#include "rocsparse.h"
#include "rocsparse_subroutine.hpp"
/*
* ===========================
* C wrapper
* ===========================
*/
extern "C" rocsparse_status rocsparse_ssubroutine(rocsparse_handle handle,
rocsparse_int m,
const float* alpha,
float* val)
{
return rocsparse_subroutine_template(handle, m, alpha, val);
}
extern "C" rocsparse_status rocsparse_dsubroutine(rocsparse_handle handle,
rocsparse_int m,
const double* alpha,
double* val)
{
return rocsparse_subroutine_template(handle, m, alpha, val);
}
extern "C" rocsparse_status rocsparse_csubroutine(rocsparse_handle handle,
rocsparse_int m,
const rocsparse_float_complex* alpha,
rocsparse_float_complex* val)
{
return rocsparse_subroutine_template(handle, m, alpha, val);
}
extern "C" rocsparse_status rocsparse_zsubroutine(rocsparse_handle handle,
rocsparse_int m,
const rocsparse_double_complex* alpha,
rocsparse_double_complex* val)
{
return rocsparse_subroutine_template(handle, m, alpha, val);
}
#pragma once
#ifndef ROCSPARSE_SUBROUTINE_HPP
#define ROCSPARSE_SUBROUTINE_HPP
#include "definitions.h"
#include "handle.h"
#include "rocsparse.h"
#include "subroutine_device.h"
#include "utility.h"
#include <hip/hip_runtime.h>
template <typename T>
__global__ void subroutine_kernel_host_pointer(rocsparse_int m, T alpha, T* val)
{
subroutine_device(m, alpha, val);
}
template <typename T>
__global__ void subroutine_kernel_device_pointer(rocsparse_int m, const T* alpha, T* val)
{
subroutine_device(m, *alpha, val);
}
template <typename T>
rocsparse_status rocsparse_subroutine_template(rocsparse_handle handle,
rocsparse_int m,
const T* alpha,
T* val)
{
// Check for valid handle
if(handle == nullptr)
{
return rocsparse_status_invalid_handle;
}
// Logging
if(handle->pointer_mode == rocsparse_pointer_mode_host)
{
log_trace(handle,
replaceX<T>("rocsparse_Xsubroutine"),
m,
*alpha,
(const void*&)val);
log_bench(handle,
"./rocsparse-bench -f subroutine -r",
replaceX<T>("X"),
"-m",
m,
"--alpha",
*alpha);
}
else
{
log_trace(handle,
replaceX<T>("rocsparse_Xsubroutine"),
m,
(const void*&)alpha,
(const void*&)val);
}
// Check size
if(m < 0)
{
return rocsparse_status_invalid_size;
}
// Quick return if possible
if(m == 0)
{
return rocsparse_status_success;
}
// Check pointer arguments
if(alpha == nullptr || val == nullptr)
{
return rocsparse_status_invalid_pointer;
}
// Differentiate between the pointer modes
if(handle->pointer_mode == rocsparse_pointer_mode_device)
{
// Launch kernel
hipLaunchKernelGGL((subroutine_kernel_device_pointer<T>),
dim3(...),
dim3(...),
0,
handle->stream,
m,
alpha,
val);
}
else
{
// Launch kernel
hipLaunchKernelGGL((subroutine_kernel_host_pointer<T>),
dim3(...),
dim3(...),
0,
handle->stream,
m,
*alpha,
val);
}
return rocsparse_status_success;
}
#endif // ROCSPARSE_SUBROUTINE_HPP
#pragma once
#ifndef SUBROUTINE_DEVICE_H
#define SUBROUTINE_DEVICE_H
#include <hip/hip_runtime.h>
template <typename T>
__device__ void subroutine_device(rocsparse_int m, T alpha, T* val)
{
...
}
#endif // SUBROUTINE_DEVICE_H
Important Functions and Data Structures#
This section describes important rocSPARSE functions and data structures.
Status-Flag Macros#
The following table lists the status-flag macros available in rocSPARSE and their purpose.
Macro |
Description |
|---|---|
|
Returns, if stat is not equal to |
|
Throws an exception, if stat is not equal to |
|
Prints an error message, if stat is not equal to |
|
Returns, if stat is not equal to |
The rocsparse_mat_info Structure#
The rocSPARSE rocsparse_mat_info is a structure holding all matrix meta information that is gathered during analysis routines.
The following table lists all currently available internal meta data structures:
Meta data structure |
Description |
|---|---|
|
Structure to hold analysis meta data for sparse matrix vector multiplication in CSR format. |
|
Structure to hold analysis meta data for operations on sparse triangular matrices, e.g. dependency graph. |
|
Structure to hold analysis meta data for sparse matrix sparse matrix multiplication in CSR format. |
Cross-Routine Data Sharing#
Already collected meta data, such as the dependency graph of a sparse matrix, can be shared among multiple routines. For example, if the incomplete LU factorization of a sparse matrix is computed, the gathered analysis data can be shared for subsequent lower triangular solves of the same matrix. This behavior can be specified by the rocsparse_analysis_policy parameter.
The following table lists subroutines that can in some cases share meta data:
Subroutine |
Sharing meta data with |
|---|---|
Note
It is important to note, that on rocSPARSE extensions, this functionality can be further expanded to improve meta data collection performance significantly.
Clients#
rocSPARSE clients host a variety of different examples as well as a unit test and benchmarking package. For detailed instructions on how to build rocSPARSE with clients, see Building and Installing.
Examples#
The examples collection offers sample implementations of the rocSPARSE API. In the following table, available examples with description, are listed.
Example |
Description |
|---|---|
example_coomv |
Perform sparse matrix vector multiplication in COO format |
example_csrmv |
Perform sparse matrix vector multiplication in CSR format |
example_ellmv |
Perform sparse matrix vector multiplication in ELL format |
example_handle |
Show rocSPARSE handle initialization and finalization |
example_hybmv |
Perform sparse matrix vector multiplication in HYB format |
Unit Tests#
Multiple unit tests are available to test for bad arguments, invalid parameters and sparse routine functionality. The unit tests are based on googletest. The tests cover all routines that are exposed by the API, including all available floating-point precision.
Benchmarks#
rocSPARSE offers a benchmarking tool that can be compiled with the clients package. The benchmark tool can perform any API exposed routine combined with time measurement. To set up a benchmark run, multiple options are available.
Command-line option |
Description |
|---|---|
help, h |
Prints the help message |
sizem, m |
Specify the m parameter, e.g. the number of rows of a sparse matrix |
sizen, n |
Specify the n parameter, e.g. the number of columns of a sparse matrix or the length of a dense vector |
sizek, k |
Specify the k parameter, e.g. the number of rows of a dense matrix |
sizennz, z |
Specify the nnz parameter, e.g. the number of non-zero entries of a sparse vector |
blockdim |
Specify the blockdim parameter, e.g. the block dimension in BSR matrices |
row-blockdimA |
Specify the row-blockdimA parameter, e.g. the row block dimension in GEBSR matrices |
col-blockdimA |
Specify the col-blockdimA parameter, e.g. the column block dimension in GEBSR matrices |
row-blockdimB |
Specify the row-blockdimB parameter, e.g. the row block dimension in GEBSR matrices |
col-blockdimB |
Specify the col-blockdimB parameter, e.g. the column block dimension in GEBSR matrices |
mtx |
Read from MatrixMarket (.mtx) format. This will override parameters m, n and z |
rocalution |
Read from rocALUTION format. This will override parameters m, n, z, mtx and laplacian-dim |
laplacian-dim |
Assemble a 2D/3D Laplacian matrix with dimensions dimx, dimy and dimz. dimz is optional. This will override parameters m, n, z and mtx |
alpha |
Specify the scalar \(\alpha\) |
beta |
Specify the scalar \(\beta\) |
transposeA |
Specify whether matrix A is (conjugate) transposed or not, see rocsparse_operation |
transposeB |
Specify whether matrix B is (conjugate) transposed or not, see rocsparse_operation |
indexbaseA |
Specify the index base of matrix A, see rocsparse_index_base |
indexbaseB |
Specify the index base of matrix B, see rocsparse_index_base |
indexbaseC |
Specify the index base of matrix C, see rocsparse_index_base |
indexbaseD |
Specify the index base of matrix D, see rocsparse_index_base |
action |
Specify whether the operation is performed symbolically or numerically, see rocsparse_action |
hybpart |
Specify the HYB partitioning type, see rocsparse_hyb_partition |
diag |
Specify the diagonal type of a sparse matrix, see rocsparse_diag_type |
uplo |
Specify the fill mode of a sparse matrix, see rocsparse_fill_mode |
storage |
Specify the storage mode of a sparse matrix, see rocsparse_storage_mode |
apolicy |
Specify the analysis policy, see rocsparse_analysis_policy |
function, f |
Specify the API exposed subroutine to benchmark |
indextype |
Index precision: integer 32 bit, integer 64 bit |
precision, r |
Floating-point precision: single real, double real, single complex, double complex |
verify, v |
Specify whether the results should be validated with the host reference implementation |
iters, i |
Iterations to run inside the timing loop |
device, d |
Set the device to be used for subsequent benchmark runs |
direction |
Specify whether BSR blocks should be laid out in row-major storage or by column-major storage |
order |
Specify whether a dense matrix is laid out in column-major or row-major storage |
format |
Specify whether a sparse matrix is laid out in coo, coo_aos, csr, csc, or ell format |
denseld |
Specify the leading dimension of a dense matrix |
batch_count |
Specify the batch count for batched routines |
batch_count_A |
Specify the batch count for batched routines |
batch_count_B |
Specify the batch count for batched routines |
batch_count_C |
Specify the batch count for batched routines |
batch_stride |
Specify the batch stride for batched routines |
memstat-report |
Specify the output filename for memory report |
spmv_alg |
Specify the algorithm to use when running SpMV |
spmm_alg |
Specify the algorithm to use when running SpMM |
gtsv_interleaved_alg |
Specify the algorithm to use when running gtsv interleaved batch routine |