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

Joo Hwan Lee, Jaewoong Sim, Hyesoon Kim
2015 2015 International Conference on Parallel Architecture and Compilation (PACT)  
In this work, we propose Bounded Staled Sync (BSSync), a hardware support for the bounded staleness consistency model, which accompanies simple logic layers in the memory hierarchy.  ...  BSSync overlaps the long latency atomic operation with the main computation, targeting iterative convergent machine learning workloads.  ...  Bounded Staleness Consistency Model BSSync supports the bounded staleness consistency model [12] to reduce the atomic operation overhead.  ... 
doi:10.1109/pact.2015.42 dblp:conf/IEEEpact/LeeSK15 fatcat:ey5nkob5uvgq3imfydkz5ist44

NERO: A Near High-Bandwidth Memory Stencil Accelerator for Weather Prediction Modeling [article]

Gagandeep Singh, Dionysios Diamantopoulos, Christoph Hagleitner, Juan Gomez-Luna, Sander Stuijk, Onur Mutlu, Henk Corporaal
2020 arXiv   pre-print
We conclude that employing near-memory acceleration solutions for weather prediction modeling is promising as a means to achieve both high performance and high energy efficiency.  ...  To overcome these challenges, we propose and evaluate the use of near-memory acceleration using a reconfigurable fabric with high-bandwidth memory (HBM).  ...  Lee et al., “BSSync: Processing Near Memory for Machine Learning Work- [28] A.  ... 
arXiv:2009.08241v1 fatcat:mj6kwwbhhne5xa7y2ilppi3ora