* feature: add blis support * feature: allow all BLA_VENDOR to be assigned in cmake arguments. align with whisper.cpp pr 927 * fix: version detection for BLA_SIZEOF_INTEGER, recover min version of cmake * Fix typo in INTEGER Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Fix: blas changes on ci --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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BLIS Installation Manual
BLIS is a portable software framework for high-performance BLAS-like dense linear algebra libraries. It has received awards and recognition, including the 2023 James H. Wilkinson Prize for Numerical Software and the 2020 SIAM Activity Group on Supercomputing Best Paper Prize. BLIS provides a new BLAS-like API and a compatibility layer for traditional BLAS routine calls. It offers features such as object-based API, typed API, BLAS and CBLAS compatibility layers.
Project URL: https://github.com/flame/blis
Prepare:
Compile BLIS:
git clone https://github.com/flame/blis
cd blis
./configure --enable-cblas -t openmp,pthreads auto
# will install to /usr/local/ by default.
make -j
Install BLIS:
sudo make install
We recommend using openmp since it's easier to modify the cores been used.
llama.cpp compilation
Makefile:
make LLAMA_BLIS=1 -j
# make LLAMA_BLIS=1 benchmark-matmult
CMake:
mkdir build
cd build
cmake -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=FLAME ..
make -j
llama.cpp execution
According to the BLIS documentation, we could set the following environment variables to modify the behavior of openmp:
export GOMP_GPU_AFFINITY="0-19"
export BLIS_NUM_THREADS=14
And then run the binaries as normal.
Intel specific issue
Some might get the error message saying that libimf.so
cannot be found.
Please follow this stackoverflow page.