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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Vydané v:	2015 International Conference on Parallel Architecture and Compilation (PACT) s. 241 - 252
Hlavní autori:	Joo Hwan Lee, Jaewoong Sim, Hyesoon Kim
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.10.2015
Predmet:	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
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