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Evaluation of intel 3D-xpoint NVDIMM technology for memory-intensive genomic workloads

Published: 30 September 2019 Publication History

Abstract

New 3D-XPoint™ technology, developed by Intel and Micron, promises to deliver high-density, lower-cost, non-volatile storage with DRAM-like performance characteristics. This paper presents a detailed empirical evaluation of Intel's Optane DC Persistent Memory solution that provides 3D-XPoint NV-DIMMs, which are directly attached to the memory bus. We evaluate general performance through a set of micro-benchmarks and also evaluate application-specific performance through measurement of a production bioinformatics workload (genome K-mer analysis). This is a memory-intensive workload that does not scale-out well with conventional data-partitioning and therefore directly benefits from increased main memory capacity. Thus, for this workload, 3D-Xpoint is key to enabling previously unattainable results. We compare performance with existing DRAM memory, evaluate different modes of operation and examine multiple integration approaches.

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cover image ACM Other conferences
MEMSYS '19: Proceedings of the International Symposium on Memory Systems
September 2019
517 pages
ISBN:9781450372060
DOI:10.1145/3357526
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 30 September 2019

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Author Tags

  1. 3DXP
  2. PCM
  3. bioinformatics
  4. genomics
  5. kmers
  6. storage class memory

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MEMSYS '19
MEMSYS '19: The International Symposium on Memory Systems
September 30 - October 3, 2019
District of Columbia, Washington, USA

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  • (2024)Achieving DRAM-Like PCM by Trading Off Capacity for LatencyIEEE Transactions on Computers10.1109/TC.2024.335577973:4(1180-1189)Online publication date: 1-Apr-2024
  • (2023)LazySortInformation Sciences: an International Journal10.1016/j.ins.2023.119137641:COnline publication date: 1-Sep-2023
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