# 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 /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_ 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