I installed MAGMA 1.5.0_beta3. My make.inc is:
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# GPU_TARGET contains one or more of Tesla, Fermi, or Kepler,
# to specify for which GPUs you want to compile MAGMA:
# Tesla - NVIDIA compute capability 1.x cards
# Fermi - NVIDIA compute capability 2.x cards
# Kepler - NVIDIA compute capability 3.x cards
# The default is all, "Tesla Fermi Kepler".
# See http://developer.nvidia.com/cuda-gpus
#
#GPU_TARGET ?= Tesla Fermi Kepler
GPU_TARGET = Tesla
CC = gcc
NVCC = nvcc
FORT = gfortran
ARCH = ar
ARCHFLAGS = cr
RANLIB = ranlib
# Defining MAGMA_ILP64 or MKL_ILP64 changes magma_int_t to int64_t in include/magma_types.h
# Compiling with -std=c++98 -pedantic finds non-standard things like variable length arrays
OPTS = -fPIC -O3 -DADD_ -Wall -fno-strict-aliasing -fopenmp -DMAGMA_WITH_MKL -DMAGMA_SETAFFINITY
F77OPTS = -fPIC -O3 -DADD_ -Wall
FOPTS = -fPIC -O3 -DADD_ -Wall -x f95-cpp-input
NVOPTS = -O3 -DADD_ -Xcompiler "-fno-strict-aliasing -fPIC"
LDOPTS = -fPIC -fopenmp
# IMPORTANT: this link line is for 64-bit int !!!!
# For regular 64-bit builds using 64-bit pointers and 32-bit int,
# use the lp64 library, not the ilp64 library. See make.inc.mkl-gcc or make.inc.mkl-icc.
# see MKL Link Advisor at http://software.intel.com/sites/products/mkl/
# gcc with MKL 10.3, GNU threads, 64-bit int
# note -DMAGMA_ILP64 or -DMKL_ILP64, and -fdefault-integer-8 in OPTS above
LIB = -lmkl_gf_ilp64 -lmkl_gnu_thread -lmkl_core -lpthread -lcublas -lcudart -lstdc++ -lm -lgfortran
# define library directories preferably in your environment, or here.
# for MKL run, e.g.: source /opt/intel/composerxe/mkl/bin/mklvars.sh intel64
#MKLROOT ?= /opt/intel/composerxe/mkl
MKLROOT = /nfs/LIBS/LIBS/mkl/l_mkl_11.1.0.080/composer_xe_2013_sp1.0.080/mkl
#CUDADIR ?= /usr/local/cuda
CUDADIR = /nfs/LIBS/LIBS/CUDA/6.0
-include make.check-mkl
-include make.check-cuda
LIBDIR = -L$(MKLROOT)/lib/intel64 \
-L$(CUDADIR)/lib64
INC = -I$(CUDADIR)/include -I$(MKLROOT)/include
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MAGMA 1.5.0 beta3 compiled for CUDA capability >= 1.0
CUDA runtime 6000, driver 6050. OpenMP threads 24. MKL 11.1.0, MKL threads 12.
device 0: Tesla K20m, 705.5 MHz clock, 4799.6 MB memory, capability 3.5
Usage: ./testing_dgemm [options] [-h|--help]
If running lapack (option --lapack), MAGMA and CUBLAS error are both computed
relative to CPU BLAS result. Else, MAGMA error is computed relative to CUBLAS result.
transA = No transpose, transB = No transpose
M N K MAGMA Gflop/s (ms) CUBLAS Gflop/s (ms) CPU Gflop/s (ms) MAGMA error CUBLAS error
=========================================================================================================
When I execute another command like ./testing_dgegqr_gpu -N 120, shows:
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MAGMA 1.5.0 beta3 compiled for CUDA capability >= 1.0
CUDA runtime 6000, driver 6050. OpenMP threads 24. MKL 11.1.0, MKL threads 12.
device 0: Tesla K20m, 705.5 MHz clock, 4799.6 MB memory, capability 3.5
Usage: ./testing_dgegqr_gpu [options] [-h|--help]
M N CPU GFlop/s (ms) GPU GFlop/s (ms) ||I-Q'Q||_F / M ||I-Q'Q||_I / M ||A-Q R||_I
MAGMA / LAPACK MAGMA / LAPACK
==========================================================================================================
Segmentation fault
Thank you, very much