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20182022
most citedFedML: A Research Library and Benchmark for Federated Machine Learning

354 citations · 835 across the 22 of their papers we have counts for

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Showing 2019 · cs.DCShow all

5 papers · 2 filters

cs.DC2019★ 2 cited

Jupiter: A Networked Computing Architecture

Pradipta Ghosh, Quynh Nguyen, Pranav K Sakulkar +7

In the era of Internet of Things, there is an increasing demand for networked computing to support the requirements of the time-constrained, compute-intensive distributed applicati…

cs.DC2019★ 1 cited

Train Where the Data is: A Case for Bandwidth Efficient Coded Training

Zhifeng Lin, Krishna Giri Narra, Mingchao Yu +2

Training a machine learning model is both compute and data-intensive. Most of the model training is performed on high performance compute nodes and the training data is stored near…

cs.DC2019

Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models

Krishna Narra, Zhifeng Lin, Ganesh Ananthanarayanan +2

Reducing the latency variance in machine learning inference is a key requirement in many applications. Variance is harder to control in a cloud deployment in the presence of stragg…

cs.DC2019★ 1 cited

PartitionedVC: Partitioned External Memory Graph Analytics Framework for SSDs

Kiran Kumar Matam, Hanieh Hashemi, Murali Annavaram

Graph analytics are at the heart of a broad range of applications such as drug discovery, page ranking, and recommendation systems. When graph size exceeds memory size, out-of-core…

cs.DC2019

Slack Squeeze Coded Computing for Adaptive Straggler Mitigation

Krishna Giri Narra, Zhifeng Lin, Mehrdad Kiamari +2

While performing distributed computations in today's cloud-based platforms, execution speed variations among compute nodes can significantly reduce the performance and create bottl…