activity
20192022
most citedSTOMP: A Tool for Evaluation of Scheduling Policies in Heterogeneous Multi-Processors

4 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AR20222 cited

HetSched: Quality-of-Mission Aware Scheduling for Autonomous Vehicle SoCs

Aporva Amarnath, Subhankar Pal, Hiwot Kassa +6

Systems-on-Chips (SoCs) that power autonomous vehicles (AVs) must meet stringent performance and safety requirements prior to deployment. With increasing complexity in AV applicati…

cs.AR20204 cited

STOMP: A Tool for Evaluation of Scheduling Policies in Heterogeneous Multi-Processors

Augusto Vega, Aporva Amarnath, John-David Wellman +6

The proliferation of heterogeneous chip multiprocessors in recent years has reached unprecedented levels. Traditional homogeneous platforms have shown fundamental limitations when…

cs.LG20201 cited

Improving Efficiency in Large-Scale Decentralized Distributed Training

Wei Zhang, Xiaodong Cui, Abdullah Kayi +9

Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchronous Parallel SGD (AD-PSGD) is a family of distributed learning algorithms that have been demonstrated to p…

cs.AR2019

Touché: Towards Ideal and Efficient Cache Compression By Mitigating Tag Area Overheads

Seokin Hong, Bulent Abali, Alper Buyuktosunoglu +2

Compression is seen as a simple technique to increase the effective cache capacity. Unfortunately, compression techniques either incur tag area overheads or restrict data placement…

eess.AS2019

A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition

Wei Zhang, Xiaodong Cui, Ulrich Finkler +6

Modern Automatic Speech Recognition (ASR) systems rely on distributed deep learning to for quick training completion. To enable efficient distributed training, it is imperative tha…