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Conference proceeding
Improving phase change memory performance with data content aware access
Proceedings of the 2020 ACM SIGPLAN International Symposium on memory management
16 Jun 2020
Abstract
Phase change memory (PCM) is a scalable non-volatile memory technology that has low access latency (like DRAM) and high capacity (like Flash). Writing to PCM incurs significantly higher latency and energy penalties compared to reading its content. A prominent characteristic of PCM's write operation is that its latency and energy are sensitive to the data to be written as well as the content that is overwritten. We observe that overwriting unknown memory content can incur significantly higher latency and energy compared to overwriting known all-zeros or all-ones content. This is because all-zeros or all-ones content is overwritten by programming the PCM cells only in one direction, i.e., using either SET or RESET operations, not both.
In this paper, we propose data content aware PCM writes (DATACON), a new mechanism that reduces the latency and energy of PCM writes by redirecting these requests to overwrite memory locations containing all-zeros or all-ones. DATACON operates in three steps. First, it estimates how much a PCM write access would benefit from overwriting known content (e.g., all-zeros, or all-ones) by comprehensively considering the number of set bits in the data to be written, and the energy-latency trade-offs for SET and RESET operations in PCM. Second, it translates the write address to a physical address within memory that contains the best type of content to overwrite, and records this translation in a table for future accesses. We exploit data access locality in work- loads to minimize the address translation overhead. Third, it re-initializes unused memory locations with known all- zeros or all-ones content in a manner that does not interfere with regular read and write accesses. DATACON overwrites unknown content only when it is absolutely necessary to do so. We evaluate DATACON with workloads from state- of-the-art machine learning applications, SPEC CPU2017, and NAS Parallel Benchmarks. Results demonstrate that DATACON improves the effective access latency by 31%, overall system performance by 27%, and total memory system energy consumption by 43% compared to the best of performance-oriented state-of-the-art techniques.
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34 citations in Scopus
Details
- Title
- Improving phase change memory performance with data content aware access
- Creators
- Shihao Song - Drexel UniversityAnup Das - Drexel UniversityOnur Mutlu - ETH Zurich, SWITZERLANDNagarajan Kandasamy - Drexel University
- Publication Details
- Proceedings of the 2020 ACM SIGPLAN International Symposium on memory management
- Series
- ISMM 2020
- Publisher
- Association for Computing Machinery (ACM)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Scopus ID
- 2-s2.0-85087106075
- Other Identifier
- 991019173546704721