Livia: Data-Centric Computing Throughout the Memory Hierarchy
Author(s)
Lockerman, Elliot; Feldmann, Axel; Bakhshalipour, Mohammad; Stanescu, Alexandru; Gupta, Shashwat; Sanchez, Daniel; Beckmann, Nathan; ... Show more Show less
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© 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM. In order to scale, future systems will need to dramatically reduce data movement. Data movement is expensive in current designs because (i) traditional memory hierarchies force computation to happen unnecessarily far away from data and (ii) processing-in-memory approaches fail to exploit locality. We propose Memory Services, a flexible programming model that enables data-centric computing throughout the memory hierarchy. In Memory Services, applications express functionality as graphs of simple tasks, each task indicating the data it operates on. We design and evaluate Livia, a new system architecture for Memory Services that dynamically schedules tasks and data at the location in the memory hierarchy that minimizes overall data movement. Livia adds less than 3% area overhead to a tiled multicore and accelerates challenging irregular workloads by 1.3× to 2.4× while reducing dynamic energy by 1.2× to 4.7×.
Date issued
2020Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryJournal
International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
Publisher
Association for Computing Machinery (ACM)
Citation
Lockerman, Elliot, Feldmann, Axel, Bakhshalipour, Mohammad, Stanescu, Alexandru, Gupta, Shashwat et al. 2020. "Livia: Data-Centric Computing Throughout the Memory Hierarchy." International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS.
Version: Final published version