# This is the configuration file to use NVBLAS Library
# Setup the environment variable NVBLAS_CONFIG_FILE to specify your own config file.
# By default, if NVBLAS_CONFIG_FILE is not defined,
# NVBLAS Library will try to open the file "nvblas.conf" in its current directory
# Example : NVBLAS_CONFIG_FILE /home/cuda_user/my_nvblas.conf
# The config file should have restricted write permissions accesses
# Specify which output log file (default is stderr)
# NVBLAS_LOGFILE nvblas.log
# Enable trace log of every intercepted BLAS calls
NVBLAS_TRACE_LOG_ENABLED
#Put here the CPU BLAS fallback Library of your choice
#It is strongly advised to use full path to describe the location of the CPU Library
NVBLAS_CPU_BLAS_LIB /usr/lib/x86_64-linux-gnu/libblas.so
#NVBLAS_CPU_BLAS_LIB <mkl_path_installtion>/libmkl_rt.so
# List of GPU devices Id to participate to the computation
# Use ALL if you want all your GPUs to contribute
# Use ALL0, if you want all your GPUs of the same type as device 0 to contribute
# However, NVBLAS consider that all GPU have the same performance and PCI bandwidth
# By default if no GPU are listed, only device 0 will be used
#NVBLAS_GPU_LIST 0 2 4
#NVBLAS_GPU_LIST ALL
NVBLAS_GPU_LIST ALL0
# Tile Dimension
NVBLAS_TILE_DIM 2048
# Autopin Memory
NVBLAS_AUTOPIN_MEM_ENABLED
#List of BLAS routines that are prevented from running on GPU (use for debugging purpose
# The current list of BLAS routines supported by NVBLAS are
# GEMM, SYRK, HERK, TRSM, TRMM, SYMM, HEMM, SYR2K, HER2K
#NVBLAS_GPU_DISABLED_SGEMM
#NVBLAS_GPU_DISABLED_DGEMM
#NVBLAS_GPU_DISABLED_CGEMM
#NVBLAS_GPU_DISABLED_ZGEMM
# Computation can be optionally hybridized between CPU and GPU
# By default, GPU-supported BLAS routines are ran fully on GPU
# The option NVBLAS_CPU_RATIO_<BLAS_ROUTINE> give the ratio [0,1]
# of the amount of computation that should be done on CPU
# CAUTION : this option should be used wisely because it can actually
# significantly reduced the overall performance if too much work is given to CPU
#NVBLAS_CPU_RATIO_CGEMM 0.07