Papers › Scalable Multi-node Fast Fourier Transform on GPUs
Scalable Multi-node Fast Fourier Transform on GPUs
Manthan Verma, Soumyadeep Chatterjee, Gaurav Garg, Bharatkumar Sharma, Nishant Arya, Shashi Kumar, Anish Saxena, Mahendra K. Verma
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In this paper, we present the details of our multi-node GPU-FFT library, as well its scaling on Selene HPC system. Our library employs slab decomposition for data division and MPI for communication among GPUs. We performed GPU-FFT on 1024³, 2048³, and 4096³ grids using a maximum of 512 A100 GPUs. We observed good scaling for 4096³ grid with 64 to 512 GPUs. We report that the timings of multicore FFT of 1536³ grid with 196608 cores of Cray XC40 is comparable to that of GPU-FFT of 2048³ grid with 128 GPUs. The efficiency of GPU-FFT is due to the fast computation capabilities of A100 card and efficient communication via NVlink.
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