Hi RTK-users, I compiled RTK with CUDA and tried to setup a benchmark to analyze the performances trend of the GPUs when using the CUDA-FDK reconstruction filter. Precisely, when reconstructing the same volume from the same data-set on NVS510 GTX860M and GTX970M i got results consistent with the number of GPUs cuda cores. Indeed, when setting up this benchmark i was expecting a reduction in the reconstruction time with the increase of cuda cores(at least until the dimension of the reconstructed volume was not the actual bottleneck). However, when testing it on a Tesla P100 i got performances comparable to the GTX860M. Would you expect such a result?
Unfortunately i am new to CUDA and i was wondering if any of you could help me figuring this out. How does rtk with CUDA manage the number of blocks/grid dimension ? Is the number of blocks/grid dimension depedent on the GPU cuda cores? Is there a way to use multiple GPUs? The test was carried with the following data: - 360 projections - reconstructed volume 600x700x800 px Thank you in advance Kind regards Elena
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