96 citations · 189 across the 12 of their papers we have counts for
27 papers
Benchmarking Resource Usage for Efficient Distributed Deep Learning
Nathan C. Frey, Baolin Li, Joseph McDonald +6
Deep learning (DL) workflows demand an ever-increasing budget of compute and energy in order to achieve outsized gains. Neural architecture searches, hyperparameter sweeps, and rap…
The MIT Supercloud Dataset
Siddharth Samsi, Matthew L Weiss, David Bestor +24
Artificial intelligence (AI) and Machine learning (ML) workloads are an increasingly larger share of the compute workloads in traditional High-Performance Computing (HPC) centers a…
Survey of Machine Learning Accelerators
Albert Reuther, Peter Michaleas, Michael Jones +3
New machine learning accelerators are being announced and released each month for a variety of applications from speech recognition, video object detection, assisted driving, and m…
Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks via Nonlinear Multigrid
Andrew C. Kirby, Siddharth Samsi, Michael Jones +3
A Multigrid Full Approximation Storage algorithm for solving Deep Residual Networks is developed to enable neural network parallelized layer-wise training and concurrent computatio…
Accuracy and Performance Comparison of Video Action Recognition Approaches
Matthew Hutchinson, Siddharth Samsi, William Arcand +16
Over the past few years, there has been significant interest in video action recognition systems and models. However, direct comparison of accuracy and computational performance re…
Multi-Temporal Analysis and Scaling Relations of 100,000,000,000 Network Packets
Jeremy Kepner, Chad Meiners, Chansup Byun +23
Our society has never been more dependent on computer networks. Effective utilization of networks requires a detailed understanding of the normal background behaviors of network tr…