GPM: Leveraging Persistent Memory from a GPU

Pandey, S and Kamath, AK and Basu, A (2022) GPM: Leveraging Persistent Memory from a GPU. In: 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2022, 28 February - 4 March 2022, Virtual, Online, pp. 142-156.

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Abstract

The GPU is a key computing platform for many application domains. While the new non-volatile memory technology has brought the promise of byte-Addressable persistence (a.k.a., persistent memory, or PM) to CPU applications, the same, unfortunately, is beyond the reach of GPU programs. We take three key steps toward enabling GPU programs to access PM directly. First, enable direct access to PM from within a GPU kernel without needing to modify the hardware. Next, we demonstrate three classes of GPU-Accelerated applications that benefit from PM. In the process, we create a workload suite with nine such applications. We then create a GPU library, written in CUDA, to support logging, checkpointing, and primitives for native persistence for programmers to easily leverage PM.

Item Type:	Conference Paper
Publication:	International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
Publisher:	Association for Computing Machinery
Additional Information:	The copyright for this article belongs to the Association for Computing Machinery.
Keywords:	Application programs; Computer graphics; Computer graphics equipment; Digital storage; Program processors, Applications domains; Check pointing; Computing platform; Crash consistency; GPU programs; GPU-accelerated; Graphic processing unit; Graphics processing; Persistent memory; Processing units, Graphics processing unit
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	11 Jul 2022 06:34
Last Modified:	11 Jul 2022 06:34
URI:	https://eprints.iisc.ac.in/id/eprint/73839

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