Generalized Data Placement Strategies for Racetrack Memories
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Ultra-dense non-volatile racetrack memories (RTMs) have been investigated at various levels in the memory hierarchy for improved performance and reduced energy consumption. However, the innate shift operations in RTMs hinder their applicability to replace low-latency on-chip memories. Recent research has demonstrated that intelligent placement of memory objects in RTMs can significantly reduce the amount of shifts with no hardware overhead, albeit for specific system setups. However, existing placement strategies may lead to sub-optimal performance when applied to different architectures. In this paper we look at generalized data placement mechanisms that improve upon existing ones by taking into account the underlying memory architecture and the timing and liveliness information of memory objects. We propose a novel heuristic and a formulation using genetic algorithms that optimize key performance parameters. We show that, on average, our generalized approach improves the number of shifts, performance and energy consumption by 4.3 ×, 46% and 55% respectively compared to the state-of-the-art.
Details
Original language | English |
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Title of host publication | 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE) |
Editors | Giorgio Di Natale, Cristiana Bolchini, Elena-Ioana Vatajelu |
Publisher | IEEE, New York [u. a.] |
Pages | 1502-1507 |
Number of pages | 6 |
ISBN (electronic) | 978-3-9819263-4-7 |
ISBN (print) | 78-1-7281-4468-9 |
Publication status | Published - Mar 2020 |
Peer-reviewed | Yes |
Publication series
Series | Design, Automation and Test in Europe Conference and Exhibition (DATE) |
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ISSN | 1530-1591 |
Conference
Title | 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020 |
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Duration | 9 - 13 March 2020 |
City | Grenoble |
Country | France |
External IDs
ORCID | /0000-0002-5007-445X/work/141545528 |
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Keywords
Research priority areas of TU Dresden
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Data placement, domain wall memory, racetrack memory, shift operations