Is there a paralleled version of LAPACKE_cheev?

Hi Chrs,

I tried linking with both libarmpl and libarmpl_mp, but I didn't notice any difference in runtime.

Is there any way to tell if this function supports multithreading or multi-core processing?

Thanks!

# without openmp
target_link_libraries(test_armpl ${CUDA_LIBRARIES} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_CUSOLVER_LIBRARIES} cublas cusolver armpl_lp64 pthread m)

# with openmp
target_link_libraries(test_armpl ${CUDA_LIBRARIES} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_CUSOLVER_LIBRARIES} cublas cusolver armpl_lp64_mp pthread m)

Hi Chrs,

I tried linking with both libarmpl and libarmpl_mp, but I didn't notice any difference in runtime.

Is there any way to tell if this function supports multithreading or multi-core processing?

Thanks!

# without openmp
target_link_libraries(test_armpl ${CUDA_LIBRARIES} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_CUSOLVER_LIBRARIES} cublas cusolver armpl_lp64 pthread m)

# with openmp
target_link_libraries(test_armpl ${CUDA_LIBRARIES} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_CUSOLVER_LIBRARIES} cublas cusolver armpl_lp64_mp pthread m)

There is no way to tell other than to notice a speedup in performance, but in this case it sounds like your problem does not currently benefit from multithreading on your system.

Chris.