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Introducing Prefetching and Data Compression to Accelerate Checkpointing for Inverse Seismic Problems
SessionResearch Posters Display
DescriptionRemote Time Migration (RTM) poses substantial computational challenges, demanding large memory and extended processing times. Our RTM implementation processes three-dimensional fields on multiple NVIDIA GPUs using the Revolve algorithm for checkpointing. However, transferring data between the host and GPU memory introduces a bottleneck.
We introduced a checkpoint prefetching mechanism to overcome this, anticipating memory transfers from host to GPU. Additionally, we integrated GPU data compression using the cuZFP library to reduce data transfer sizes further. The experimental results demonstrated significant performance improvements, achieving a speedup of 1.98x - 2.53x in our benchmark dataset. Prefetching + compression techniques together could reduce host-to-GPU memory transfers by up to 16x.
We introduced a checkpoint prefetching mechanism to overcome this, anticipating memory transfers from host to GPU. Additionally, we integrated GPU data compression using the cuZFP library to reduce data transfer sizes further. The experimental results demonstrated significant performance improvements, achieving a speedup of 1.98x - 2.53x in our benchmark dataset. Prefetching + compression techniques together could reduce host-to-GPU memory transfers by up to 16x.
Event Type
Posters
Research Posters
TimeTuesday, 14 November 202310am - 5pm MST
LocationDEF Concourse
TP
XO/EX