BSSync: Processing Near Memory for Machine Learning Workloads with Bounded Staleness Consistency Models

Parallel machine learning workloads have become prevalent in numerous application domains. Many of these workloads are iterative convergent, allowing different threads to compute in an asynchronous manner, relaxing certain read-after-write data dependencies to use stale values. While considerable ef...

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Veröffentlicht in:	2015 International Conference on Parallel Architecture and Compilation (PACT) S. 241 - 252
Hauptverfasser:	Joo Hwan Lee, Jaewoong Sim, Hyesoon Kim
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2015
Schlagworte:	Asynchronous Parallelism Atomic layer deposition Atomic Operation Bounded Staleness Consistency Model Computational modeling Convergence Hardware Instruction sets Iterative Convergent Machine Learning Workloads Parallel processing Synchronization
ISSN:	1089-795X
Online-Zugang:	Volltext
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