This document describes which routines are supported in CLBlast. For other information about CLBlast, see the main README.
Full API documentation is available in a separate API documentation file.
The different data-types supported by the library are:
- S: Single-precision 32-bit floating-point (
float). - D: Double-precision 64-bit floating-point (
double). - C: Complex single-precision 2x32-bit floating-point (
std::complex<float>). - Z: Complex double-precision 2x64-bit floating-point (
std::complex<double>). - H: Half-precision 16-bit floating-point (
cl_half). See section 'Half precision' below for more information.
CLBlast supports almost all the Netlib BLAS routines plus a couple of extra non-BLAS routines. The supported BLAS routines are marked with '✔' in the following tables. Routines marked with '-' do not exist: they are not part of BLAS at all.
| Level-1 | S | D | C | Z | H |
|---|---|---|---|---|---|
| xSWAP | ✔ | ✔ | ✔ | ✔ | ✔ |
| xSCAL | ✔ | ✔ | ✔ | ✔ | ✔ |
| xCOPY | ✔ | ✔ | ✔ | ✔ | ✔ |
| xAXPY | ✔ | ✔ | ✔ | ✔ | ✔ |
| xDOT | ✔ | ✔ | - | - | ✔ |
| xDOTU | - | - | ✔ | ✔ | - |
| xDOTC | - | - | ✔ | ✔ | - |
| xNRM2 | ✔ | ✔ | ✔ | ✔ | ✔ |
| xASUM | ✔ | ✔ | ✔ | ✔ | ✔ |
| IxAMAX | ✔ | ✔ | ✔ | ✔ | ✔ |
| Level-2 | S | D | C | Z | H |
|---|---|---|---|---|---|
| xGEMV | ✔ | ✔ | ✔ | ✔ | ✔ |
| xGBMV | ✔ | ✔ | ✔ | ✔ | ✔ |
| xHEMV | - | - | ✔ | ✔ | - |
| xHBMV | - | - | ✔ | ✔ | - |
| xHPMV | - | - | ✔ | ✔ | - |
| xSYMV | ✔ | ✔ | - | - | ✔ |
| xSBMV | ✔ | ✔ | - | - | ✔ |
| xSPMV | ✔ | ✔ | - | - | ✔ |
| xTRMV | ✔ | ✔ | ✔ | ✔ | ✔ |
| xTBMV | ✔ | ✔ | ✔ | ✔ | ✔ |
| xTPMV | ✔ | ✔ | ✔ | ✔ | ✔ |
| xGER | ✔ | ✔ | - | - | ✔ |
| xGERU | - | - | ✔ | ✔ | - |
| xGERC | - | - | ✔ | ✔ | - |
| xHER | - | - | ✔ | ✔ | - |
| xHPR | - | - | ✔ | ✔ | - |
| xHER2 | - | - | ✔ | ✔ | - |
| xHPR2 | - | - | ✔ | ✔ | - |
| xSYR | ✔ | ✔ | - | - | ✔ |
| xSPR | ✔ | ✔ | - | - | ✔ |
| xSYR2 | ✔ | ✔ | - | - | ✔ |
| xSPR2 | ✔ | ✔ | - | - | ✔ |
| xTRSV | ✔ | ✔ | ✔ | ✔ |
| Level-3 | S | D | C | Z | H |
|---|---|---|---|---|---|
| xGEMM | ✔ | ✔ | ✔ | ✔ | ✔ |
| xSYMM | ✔ | ✔ | ✔ | ✔ | ✔ |
| xHEMM | - | - | ✔ | ✔ | - |
| xSYRK | ✔ | ✔ | ✔ | ✔ | ✔ |
| xHERK | - | - | ✔ | ✔ | - |
| xSYR2K | ✔ | ✔ | ✔ | ✔ | ✔ |
| xHER2K | - | - | ✔ | ✔ | - |
| xTRMM | ✔ | ✔ | ✔ | ✔ | ✔ |
| xTRSM | ✔ | ✔ | ✔ | ✔ |
Furthermore, there are also batched versions of BLAS routines available, processing multiple smaller computations in one go for better performance:
| Batched | S | D | C | Z | H |
|---|---|---|---|---|---|
| xAXPYBATCHED | ✔ | ✔ | ✔ | ✔ | ✔ |
| xGEMMBATCHED | ✔ | ✔ | ✔ | ✔ | ✔ |
| xGEMMSTRIDEDBATCHED | ✔ | ✔ | ✔ | ✔ | ✔ |
In addition, some extra non-BLAS routines are also supported by CLBlast, classified as level-X. They are experimental and should be used with care:
| Level-X | S | D | C | Z | H |
|---|---|---|---|---|---|
| xSUM | ✔ | ✔ | ✔ | ✔ | ✔ |
| IxAMIN | ✔ | ✔ | ✔ | ✔ | ✔ |
| IxMAX | ✔ | ✔ | ✔ | ✔ | ✔ |
| IxMIN | ✔ | ✔ | ✔ | ✔ | ✔ |
| xHAD | ✔ | ✔ | ✔ | ✔ | ✔ |
| xOMATCOPY | ✔ | ✔ | ✔ | ✔ | ✔ |
| xIM2COL | ✔ | ✔ | ✔ | ✔ | ✔ |
| xCOL2IM | ✔ | ✔ | ✔ | ✔ | ✔ |
| xCONVGEMM | ✔ | ✔ | - | - | ✔ |
Some less commonly used BLAS routines are not yet supported by CLBlast. They are xROTG, xROTMG, xROT, xROTM, xTBSV, and xTPSV.
The half-precision fp16 format is a 16-bits floating-point data-type. Some OpenCL devices support the cl_khr_fp16 extension, reducing storage and bandwidth requirements by a factor 2 compared to single-precision floating-point. In case the hardware also accelerates arithmetic on half-precision data-types, this can also greatly improve compute performance of e.g. level-3 routines such as GEMM. Devices which can benefit from this are among others Intel GPUs, ARM Mali GPUs, and NVIDIA's latest Pascal GPUs. Half-precision is in particular interest for the deep-learning community, in which convolutional neural networks can be processed much faster at a minor accuracy loss.
Since there is no half-precision data-type in C or C++, OpenCL provides the cl_half type for the host device. Unfortunately, internally this translates to a 16-bits integer, so computations on the host using this data-type should be avoided. For convenience, CLBlast provides the clblast_half.h header (C99 and C++ compatible), defining the half type as a short-hand to cl_half and the following basic functions:
half FloatToHalf(const float value): Converts a 32-bits floating-point value to a 16-bits floating-point value.float HalfToFloat(const half value): Converts a 16-bits floating-point value to a 32-bits floating-point value.
The samples/haxpy.c example shows how to use these convenience functions when calling the half-precision BLAS routine HAXPY.