272 citations · 1.8k across the 82 of their papers we have counts for
12 papers · 1 filter
Large Scale Parallelization Using File-Based Communications
Chansup Byun, Jeremy Kepner, William Arcand +14
In this paper, we present a novel and new file-based communication architecture using the local filesystem for large scale parallelization. This new approach eliminates the issues…
Sparse Deep Neural Network Graph Challenge
Jeremy Kepner, Simon Alford, Vijay Gadepally +4
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…
Survey and Benchmarking of Machine Learning Accelerators
Albert Reuther, Peter Michaleas, Michael Jones +3
Advances in multicore processors and accelerators have opened the flood gates to greater exploration and application of machine learning techniques to a variety of applications. Th…
TapirXLA: Embedding Fork-Join Parallelism into the XLA Compiler in TensorFlow Using Tapir
Tao B. Schardl, Siddharth Samsi
This work introduces TapirXLA, a replacement for TensorFlow's XLA compiler that embeds recursive fork-join parallelism into XLA's low-level representation of code. Machine-learning…
Distributed Deep Learning for Precipitation Nowcasting
Siddharth Samsi, Christopher J. Mattioli, Mark S. Veillette
Effective training of Deep Neural Networks requires massive amounts of data and compute. As a result, longer times are needed to train complex models requiring large datasets, whic…
Securing HPC using Federated Authentication
Andrew Prout, William Arcand, David Bestor +15
Federated authentication can drastically reduce the overhead of basic account maintenance while simultaneously improving overall system security. Integrating with the user's more f…
Large Scale Organization and Inference of an Imagery Dataset for Public Safety
Jeffrey Liu, David Strohschein, Siddharth Samsi +1
Video applications and analytics are routinely projected as a stressing and significant service of the Nationwide Public Safety Broadband Network. As part of a NIST PSCR funded eff…
Streaming 1.9 Billion Hypersparse Network Updates per Second with D4M
Jeremy Kepner, Vijay Gadepally, Lauren Milechin +15
The Dynamic Distributed Dimensional Data Model (D4M) library implements associative arrays in a variety of languages (Python, Julia, and Matlab/Octave) and provides a lightweight i…
Optimizing Xeon Phi for Interactive Data Analysis
Chansup Byun, Jeremy Kepner, William Arcand +15
The Intel Xeon Phi manycore processor is designed to provide high performance matrix computations of the type often performed in data analysis. Common data analysis environments in…
AI Enabling Technologies: A Survey
Vijay Gadepally, Justin Goodwin, Jeremy Kepner +5
Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of ev…
Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers
Julia Mullen, Albert Reuther, William Arcand +15
For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and al…
A Billion Updates per Second Using 30,000 Hierarchical In-Memory D4M Databases
Jeremy Kepner, Vijay Gadepally, Lauren Milechin +15
Analyzing large scale networks requires high performance streaming updates of graph representations of these data. Associative arrays are mathematical objects combining properties…