Hi Freddie, thanks a lot for your answer
I have run Coutte Flow 2D with 3 calculation mode and it gives an unique
result.
Case 1 : Run with all core in CPU ( 8 cores in 1 processor )
pyfr run -b openmp -p coutte_flow_2d.pyfrm coutte_flow_2d.ini
Calculation time : 00:08:40
Case 2 : Run with 1 core in CPU with CUDA Backend
pyfr run -b cuda -p couttle_flow_2d.pyfrm coutte_flow_2d.ini
Calculation time : 00.05.57
Last, i've done your suggestion to do
$ export OMP_NUM_THREADS=1 to run the case in single core
Case 3 : $ export OMP_NUM_THREADS=1
pyfr run -b openmp -p coutte_flow_2d.pyfrm coutte_flow_2d.ini
Calculation time : 00:04:24
Is it weird? The single core processing led to fastest calculation time. Is
there a need to match the case with the backend? I mean some simple cases
maybe are suitable with low hardware configuration while more complex cases
are fit with high performance hardware configuration. Is it true?
Second question, how can i run PyFR in 1 CPU ( Intel Core i7) with all its
cores ( 8 cores ) + 1 GPU ( Nvidia GeForce GTX460). What command do i have
to write? Assume i have installed OpenMP,OpenCL,and CUDA Backend.
Thank you for giving attention to my questions, Freddie and all PyFR
Developers.
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