activity
20142026
most citedInteractive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis

272 citations · 2.5k across the 136 of their papers we have counts for

collaborators
Showing 2019Show all

13 papers · 1 filter

cs.CR2019

Survey of Attacks and Defenses on Edge-Deployed Neural Networks

Mihailo Isakov, Vijay Gadepally, Karen M. Gettings +1

Deep Neural Network (DNN) workloads are quickly moving from datacenters onto edge devices, for latency, privacy, or energy reasons. While datacenter networks can be protected using…

cs.DC2019★ 8 cited

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…

cs.CV2019★ 40 cited

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…

cs.PF2019★ 174 cited

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…

cs.PF2019★ 2 cited

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…

cs.DC2019★ 3 cited

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…

cs.DC2019★ 14 cited

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…

cs.PF2019★ 8 cited

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…

cs.AI2019★ 6 cited

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…

cs.DB2019★ 26 cited

RedisGraph GraphBLAS Enabled Graph Database

Pieter Cailliau, Tim Davis, Vijay Gadepally +4

RedisGraph is a Redis module developed by Redis Labs to add graph database functionality to the Redis database. RedisGraph represents connected data as adjacency matrices. By repre…

cs.NI2019★ 19 cited

Hypersparse Neural Network Analysis of Large-Scale Internet Traffic

Jeremy Kepner, Kenjiro Cho, KC Claffy +3

The Internet is transforming our society, necessitating a quantitative understanding of Internet traffic. Our team collects and curates the largest publicly available Internet traf…

cs.DC2019★ 5 cited

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…

cs.DB2019★ 5 cited

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…