272 citations · 1.5k across the 62 of their papers we have counts for
9 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…
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…
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…