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+
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+
## Introduction
-OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version.
+OpenBLAS is an optimized BLAS (Basic Linear Algebra Subprograms) library based on GotoBLAS2 1.13 BSD version.
Please read the documentation on the OpenBLAS wiki pages: <https://github.com/xianyi/OpenBLAS/wiki>.
+For a general introduction to the BLAS routines, please refer to the extensive documentation of their reference implementation hosted at netlib:
+<https://www.netlib.org/blas>. On that site you will likewise find documentation for the reference implementation of the higher-level library LAPACK - the **L**inear **A**lgebra **Pack**age that comes included with OpenBLAS. If you are looking for a general primer or refresher on Linear Algebra, the set of six
+20-minute lecture videos by Prof. Gilbert Strang on either MIT OpenCourseWare <https://ocw.mit.edu/resources/res-18-010-a-2020-vision-of-linear-algebra-spring-2020/> or Youtube <https://www.youtube.com/playlist?list=PLUl4u3cNGP61iQEFiWLE21EJCxwmWvvek> may be helpful.
+
## Binary Packages
We provide official binary packages for the following platform:
* Windows x86/x86_64
-You can download them from [file hosting on sourceforge.net](https://sourceforge.net/projects/openblas/files/).
+You can download them from [file hosting on sourceforge.net](https://sourceforge.net/projects/openblas/files/) or from the Releases section of the github project page, [https://github.com/xianyi/OpenBLAS/releases](https://github.com/xianyi/OpenBLAS/releases).
## Installation from Source
Download from project homepage, https://xianyi.github.com/OpenBLAS/, or check out the code
-using Git from https://github.com/xianyi/OpenBLAS.git.
+using Git from https://github.com/xianyi/OpenBLAS.git. (If you want the most up to date version, be
+sure to use the develop branch - master is several years out of date due to a change of maintainership.)
Buildtime parameters can be chosen in Makefile.rule, see there for a short description of each option.
Most can also be given directly on the make or cmake command line.
Simply invoking `make` (or `gmake` on BSD) will detect the CPU automatically.
To set a specific target CPU, use `make TARGET=xxx`, e.g. `make TARGET=NEHALEM`.
-The full target list is in the file `TargetList.txt`.
+The full target list is in the file `TargetList.txt`. For building with `cmake`, the
+usual conventions apply, i.e. create a build directory either underneath the toplevel
+OpenBLAS source directory or separate from it, and invoke `cmake` there with the path
+to the source tree and any build options you plan to set.
### Cross compile
```sh
make BINARY=64 CC=mips64el-unknown-linux-gnu-gcc FC=mips64el-unknown-linux-gnu-gfortran HOSTCC=gcc TARGET=LOONGSON3A
```
+ or same with the newer mips-crosscompiler put out by Loongson that defaults to the 32bit ABI:
+ ```sh
+ make HOSTCC=gcc CC='/opt/mips-loongson-gcc7.3-linux-gnu/2019.06-29/bin/mips-linux-gnu-gcc -mabi=64' FC='/opt/mips-loongson-gcc7.3-linux-gnu/2019.06-29/bin/mips-linux-gnu-gfortran -mabi=64' TARGET=LOONGSON3A
+ ```
* On an x86 box, compile this library for a loongson3a CPU with loongcc (based on Open64) compiler:
```sh
- **Intel Sandy Bridge**: Optimized Level-3 and Level-2 BLAS with AVX on x86-64.
- **Intel Haswell**: Optimized Level-3 and Level-2 BLAS with AVX2 and FMA on x86-64.
- **Intel Skylake-X**: Optimized Level-3 and Level-2 BLAS with AVX512 and FMA on x86-64.
+- **Intel Cooper Lake**: as Skylake-X with improved BFLOAT16 support.
- **AMD Bobcat**: Used GotoBLAS2 Barcelona codes.
- **AMD Bulldozer**: x86-64 ?GEMM FMA4 kernels. (Thanks to Werner Saar)
- **AMD PILEDRIVER**: Uses Bulldozer codes with some optimizations.
- **AMD STEAMROLLER**: Uses Bulldozer codes with some optimizations.
- **AMD ZEN**: Uses Haswell codes with some optimizations.
+#### MIPS32
+
+- **MIPS 1004K**: uses P5600 codes
+- **MIPS 24K**: uses P5600 codes
+
#### MIPS64
- **ICT Loongson 3A**: Optimized Level-3 BLAS and the part of Level-1,2.
- **ARMv8**: Basic ARMV8 with small caches, optimized Level-3 and Level-2 BLAS
- **Cortex-A53**: same as ARMV8 (different cpu specifications)
+- **Cortex-A55**: same as ARMV8 (different cpu specifications)
- **Cortex A57**: Optimized Level-3 and Level-2 functions
- **Cortex A72**: same as A57 ( different cpu specifications)
- **Cortex A73**: same as A57 (different cpu specifications)
- **Falkor**: same as A57 (different cpu specifications)
- **ThunderX**: Optimized some Level-1 functions
- **ThunderX2T99**: Optimized Level-3 BLAS and parts of Levels 1 and 2
+- **ThunderX3T110**
- **TSV110**: Optimized some Level-3 helper functions
+- **EMAG 8180**: preliminary support based on A57
+- **Neoverse N1**: (AWS Graviton2) preliminary support
+- **Apple Vortex**: preliminary support based on ARMV8
#### PPC/PPC64
- **POWER8**: Optimized BLAS, only for PPC64LE (Little Endian), only with `USE_OPENMP=1`
- **POWER9**: Optimized Level-3 BLAS (real) and some Level-1,2. PPC64LE with OpenMP only.
+- **POWER10**:
#### IBM zEnterprise System
- **Z13**: Optimized Level-3 BLAS and Level-1,2
- **Z14**: Optimized Level-3 BLAS and (single precision) Level-1,2
+#### RISC-V
+
+- **C910V**: Optimized Level-3 BLAS (real) and Level-1,2 by RISC-V Vector extension 0.7.1.
+ ```sh
+ make HOSTCC=gcc TARGET=C910V CC=riscv64-unknown-linux-gnu-gcc FC=riscv64-unknown-linux-gnu-gfortran
+ ```
+ (also known to work on C906)
+
### Support for multiple targets in a single library
-OpenBLAS can be built for multiple targets with runtime detection of the target cpu by specifiying DYNAMIC_ARCH=1 in Makefile.rule, on the gmake command line or as -DDYNAMIC_ARCH=TRUE in cmake.
-For **x86_64**, the list of targets this activates contains Prescott, Core2, Nehalem, Barcelona, Sandybridge, Bulldozer, Piledriver, Steamroller, Excavator, Haswell, Zen, SkylakeX. For cpu generations not included in this list, the corresponding older model is used. If you also specify DYNAMIC_OLDER=1, specific support for Penryn, Dunnington, Opteron, Opteron/SSE3, Bobcat, Atom and Nano is added. Finally there is an option DYNAMIC_LIST that allows to specify an individual list of targets to include instead of the default.
-DYNAMIC_ARCH is also supported on **x86**, where it translates to Katmai, Coppermine, Northwood, Prescott, Banias,
+OpenBLAS can be built for multiple targets with runtime detection of the target cpu by specifiying `DYNAMIC_ARCH=1` in Makefile.rule, on the gmake command line or as `-DDYNAMIC_ARCH=TRUE` in cmake.
+
+For **x86_64**, the list of targets this activates contains Prescott, Core2, Nehalem, Barcelona, Sandybridge, Bulldozer, Piledriver, Steamroller, Excavator, Haswell, Zen, SkylakeX. For cpu generations not included in this list, the corresponding older model is used. If you also specify `DYNAMIC_OLDER=1`, specific support for Penryn, Dunnington, Opteron, Opteron/SSE3, Bobcat, Atom and Nano is added. Finally there is an option `DYNAMIC_LIST` that allows to specify an individual list of targets to include instead of the default.
+
+`DYNAMIC_ARCH` is also supported on **x86**, where it translates to Katmai, Coppermine, Northwood, Prescott, Banias,
Core2, Penryn, Dunnington, Nehalem, Athlon, Opteron, Opteron_SSE3, Barcelona, Bobcat, Atom and Nano.
+
On **ARMV8**, it enables support for CortexA53, CortexA57, CortexA72, CortexA73, Falkor, ThunderX, ThunderX2T99, TSV110 as well as generic ARMV8 cpus.
+
For **POWER**, the list encompasses POWER6, POWER8 and POWER9, on **ZARCH** it comprises Z13 and Z14.
-The TARGET option can be used in conjunction with DYNAMIC_ARCH=1 to specify which cpu model should be assumed for all the
+
+The `TARGET` option can be used in conjunction with `DYNAMIC_ARCH=1` to specify which cpu model should be assumed for all the
common code in the library, usually you will want to set this to the oldest model you expect to encounter.
-Please not that it is not possible to combine support for different architectures, so no combined 32 and 64 bit or x86_64 and arm64 in the same library.
+Please note that it is not possible to combine support for different architectures, so no combined 32 and 64 bit or x86_64 and arm64 in the same library.
### Supported OS
- **Android**: Supported by the community. Please read <https://github.com/xianyi/OpenBLAS/wiki/How-to-build-OpenBLAS-for-Android>.
- **AIX**: Supported on PPC up to POWER8
- **Haiku**: Supported by the community. We don't actively test the library on this OS.
-- **SunOS**: Supported by the community. We don't actively test the library on this OS:
+- **SunOS**: Supported by the community. We don't actively test the library on this OS.
+- **Cortex-M**: Supported by the community. Please read <https://github.com/xianyi/OpenBLAS/wiki/How-to-use-OpenBLAS-on-Cortex-M>.
## Usage
void goto_set_num_threads(int num_threads);
void openblas_set_num_threads(int num_threads);
```
-
+Note that these are only used once at library initialization, and are not available for
+fine-tuning thread numbers in individual BLAS calls.
If you compile this library with `USE_OPENMP=1`, you should use the above functions too.
## Reporting bugs
* Please use Clang version 3.1 and above to compile the library on Sandy Bridge microarchitecture.
Clang 3.0 will generate the wrong AVX binary code.
* Please use GCC version 6 or LLVM version 6 and above to compile Skylake AVX512 kernels.
-* The number of CPUs/cores should less than or equal to 256. On Linux `x86_64` (`amd64`),
+* The number of CPUs/cores should be less than or equal to 256. On Linux `x86_64` (`amd64`),
there is experimental support for up to 1024 CPUs/cores and 128 numa nodes if you build
the library with `BIGNUMA=1`.
* OpenBLAS does not set processor affinity by default.
projects / platform / upstream / openblas.git / blobdiff