272 citations · 1.8k across the 82 of their papers we have counts for
11 papers · 1 filter
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…
Compute, Time and Energy Characterization of Encoder-Decoder Networks with Automatic Mixed Precision Training
Siddharth Samsi, Michael Jones, Mark M. Veillette
Deep neural networks have shown great success in many diverse fields. The training of these networks can take significant amounts of time, compute and energy. As datasets get large…
Benchmarking network fabrics for data distributed training of deep neural networks
Siddharth Samsi, Andrew Prout, Michael Jones +16
Artificial Intelligence/Machine Learning applications require the training of complex models on large amounts of labelled data. The large computational requirements for training de…
Best of Both Worlds: High Performance Interactive and Batch Launching
Chansup Byun, Jeremy Kepner, William Arcand +16
Rapid launch of thousands of jobs is essential for effective interactive supercomputing, big data analysis, and AI algorithm development. Achieving thousands of launches per second…
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…
GraphChallenge.org Sparse Deep Neural Network Performance
Jeremy Kepner, Simon Alford, Vijay Gadepally +5
The MIT/IEEE/Amazon GraphChallenge.org encourages community approaches to developing new solutions for analyzing graphs and sparse data. Sparse AI analytics present unique scalabil…
GraphChallenge.org Triangle Counting Performance
Siddharth Samsi, Jeremy Kepner, Vijay Gadepally +9
The rise of graph analytic systems has created a need for new ways to measure and compare the capabilities of graph processing systems. The MIT/Amazon/IEEE Graph Challenge has been…
AI Data Wrangling with Associative Arrays
Jeremy Kepner, Vijay Gadepally, Hayden Jananthan +2
The AI revolution is data driven. AI "data wrangling" is the process by which unusable data is transformed to support AI algorithm development (training) and deployment (inference)…
75,000,000,000 Streaming Inserts/Second Using Hierarchical Hypersparse GraphBLAS Matrices
Jeremy Kepner, Tim Davis, Chansup Byun +16
The SuiteSparse GraphBLAS C-library implements high performance hypersparse matrices with bindings to a variety of languages (Python, Julia, and Matlab/Octave). GraphBLAS provides…