GPU+DPU for Computational Storage

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Wednesday, May 25, 2022
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One of the challenges for computational storage is getting flexible and powerful compute close enough to the storage to make it worthwhile. FPGAs have potential but are hard to program and not very flexible. Traditional CPU complexes have a large footprint and lack the parallel processing abilities ideal for AI/ML applications. Data Processing Units (DPUs) tightly coupled with GPUs are the answer. The DPU integrates a CPU and hardware accelerators for IO, and storage into a single chip. At the same time, the GPU provides for rapid computation of multiple parallel processes from a single chip, which is beneficial for computational storage applications, including AI. This talk will detail a GPU+DPU solution along with the use cases that it will enable.

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