Livia: Data-Centric Computing Throughout the Memory Hierarchy
© 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 a...
Main Authors: | Lockerman, Elliot, Feldmann, Axel, Bakhshalipour, Mohammad, Stanescu, Alexandru, Gupta, Shashwat, Sanchez, Daniel, Beckmann, Nathan |
---|---|
Format: | Article |
Language: | English |
Published: |
Association for Computing Machinery (ACM)
2022
|
Online Access: | https://hdl.handle.net/1721.1/143865 |
Similar Items
-
Livia: Data-Centric Computing Throughout the Memory Hierarchy
by: Lockerman, Elliot, et al.
Published: (2022) -
Jenga: Harnessing Heterogeneous Memories through Reconfigurable Cache Hierarchies
by: Beckmann, Nathan, et al.
Published: (2015) -
Scaling Distributed Cache Hierarchies through Computation and Data Co-Scheduling
by: Beckmann, Nathan Zachary, et al.
Published: (2015) -
Jenga: Software-Defined Cache Hierarchies
by: Tsai, Po-An, et al.
Published: (2021) -
Rethinking the Memory Hierarchy for Modern Languages
by: Tsai, Po-An, et al.
Published: (2020)