Crystal: A design-time resource partitioning method for hybrid main memory

Dmitry Knyaginin, Georgi N. Gaydadjiev, Per Stenström

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

Non-Volatile Memory (NVM) technologies can be used to reduce system-level execution time, energy, or cost but they add a new design dimension. Finding the best amounts of DRAM and NVM in hybrid main memory systems is a nontrivial design-time issue, the best solution to which depends on many factors. Such resource partitioning between DRAM and NVM can be framed as an optimization problem where the minimum of a target metric is sought, trends matter more than absolute values, and thus the precision of detailed modeling is overkill. Here we present Crystal, an analytic approach to early and rapid design-time resource partitioning of hybrid main memories. Crystal provides first-order estimates of system-level execution time and energy, sufficient to enable exhaustive search of the best amount and type of NVM for given workloads and partitioning goals. Crystal thus helps system designers to quickly find the most promising hybrid configurations for detailed evaluation. E.g., Crystal shows how for specific workloads higher system-level performance and energy efficiency can be achieved by employing an NVM with the speed and energy consumption of NAND Flash instead of a much faster and more energy efficient NVM like phase-change memory.

Original languageEnglish
Title of host publicationProceedings - 43rd International Conference on Parallel Processing, ICPP 2014
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages90-100
Number of pages11
EditionNovember
ISBN (Electronic)9781479956180
DOIs
Publication statusPublished - 13 Nov 2014
Externally publishedYes
Event43rd International Conference on Parallel Processing, ICPP 2014 - Minneapolis, United States
Duration: 9 Sept 201412 Sept 2014

Publication series

NameProceedings of the International Conference on Parallel Processing
NumberNovember
Volume2014-November
ISSN (Print)0190-3918

Conference

Conference43rd International Conference on Parallel Processing, ICPP 2014
Country/TerritoryUnited States
CityMinneapolis
Period9/09/1412/09/14

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