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NVIDIA, IBM have a plan to connect GPUs straight to SSDs

Posted on May 16, 2022 by Agitator!!

In a research paper published by Cornell, a case is made for enabling fine-grain High Throughput GPU-Orchestrated Access to storage or cutting out the middle man overhead.

Unfortunately, such a CPU-centric strategy causes excessive CPU-GPU synchronization overhead and/or I/O traffic amplification, diminishing the effective storage bandwidth for emerging applications with fine-grain data-dependent access patterns like graph and data analytics, recommender systems, and graph neural networks. In this work, we make a case for enabling GPUs to orchestrate high-throughput, fine-grain accesses into NVMe Solid State Drives (SSDs) in a new system architecture called BaM. BaM mitigates the I/O traffic amplification by enabling the GPU threads to read or write small amounts of data on-demand, as determined by the compute. We show that (1) the BaM infrastructure software running on GPUs can identify and communicate the fine-grain accesses at a sufficiently high rate to fully utilize the underlying storage devices, (2) even with consumer-grade SSDs, a BaM system can support application performance that is competitive against a much more expensive DRAM-only solution, and (3) the reduction in I/O amplification can yield significant performance benefit.

For more, check out this Cornell University story.

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