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20082024
most citedAlgorithmic Based Fault Tolerance Applied to High Performance Computing

20 citations · 51 across the 10 of their papers we have counts for

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Showing cs.DCShow all

8 papers · 1 filter

cs.DC2022★ 5 cited

Implicit Actions and Non-blocking Failure Recovery with MPI

Aurelien Bouteiller, George Bosilca

Scientific applications have long embraced the MPI as the environment of choice to execute on large distributed systems. The User-Level Failure Mitigation (ULFM) specification exte…

cs.DC2021★ 15 cited

Callback-based Completion Notification using MPI Continuations

Joseph Schuchart, Philipp Samfass, Christoph Niethammer +2

Asynchronous programming models (APM) are gaining more and more traction, allowing applications to expose the available concurrency to a runtime system tasked with coordinating the…

cs.DC2021

Quo Vadis MPI RMA? Towards a More Efficient Use of MPI One-Sided Communication

Joseph Schuchart, Christoph Niethammer, José Gracia +1

The MPI standard has long included one-sided communication abstractions through the MPI Remote Memory Access (RMA) interface. Unfortunately, the MPI RMA chapter in the 4.0 version…

cs.DC2019

Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime Performance

Elliott Slaughter, Wei Wu, Yuankun Fu +12

We present Task Bench, a parameterized benchmark designed to explore the performance of parallel and distributed programming systems under a variety of application scenarios. Task…

cs.DC2018★ 3 cited

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks

Linnan Wang, Wei Wu, Junyu Zhang +4

The performance and efficiency of distributed training of Deep Neural Networks highly depend on the performance of gradient averaging among all participating nodes, which is bounde…

cs.DC2016★ 5 cited

Efficient Communications in Training Large Scale Neural Networks

Linnan Wang, Wei Wu, George Bosilca +2

We consider the problem of how to reduce the cost of communication that is required for the parallel training of a neural network. The state-of-the-art method, Bulk Synchronous Par…