272 citations · 476 across the 32 of their papers we have counts for
32 papers
Mapping of Internet "Coastlines" via Large Scale Anonymized Network Source Correlations
Hayden Jananthan, Jeremy Kepner, Michael Jones +25
Expanding the scientific tools available to protect computer networks can be aided by a deeper understanding of the underlying statistical distributions of network traffic and thei…
pPython Performance Study
Chansup Byun, William Arcand, David Bestor +17
pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics…
Focusing and Calibration of Large Scale Network Sensors using GraphBLAS Anonymized Hypersparse Matrices
Jeremy Kepner, Michael Jones, Phil Dykstra +23
Defending community-owned cyber space requires community-based efforts. Large-scale network observations that uphold the highest regard for privacy are key to protecting our shared…
Deployment of Real-Time Network Traffic Analysis using GraphBLAS Hypersparse Matrices and D4M Associative Arrays
Michael Jones, Jeremy Kepner, Andrew Prout +20
Matrix/array analysis of networks can provide significant insight into their behavior and aid in their operation and protection. Prior work has demonstrated the analytic, performan…
Hypersparse Network Flow Analysis of Packets with GraphBLAS
Tyler Trigg, Chad Meiners, Sandeep Pisharody +23
Internet analysis is a major challenge due to the volume and rate of network traffic. In lieu of analyzing traffic as raw packets, network analysts often rely on compressed network…
Python Implementation of the Dynamic Distributed Dimensional Data Model
Hayden Jananthan, Lauren Milechin, Michael Jones +17
Python has become a standard scientific computing language with fast-growing support of machine learning and data analysis modules, as well as an increasing usage of big data. The…
pPython for Parallel Python Programming
Chansup Byun, William Arcand, David Bestor +18
pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics…
The MIT Supercloud Workload Classification Challenge
Benny J. Tang, Qiqi Chen, Matthew L. Weiss +24
High-Performance Computing (HPC) centers and cloud providers support an increasingly diverse set of applications on heterogenous hardware. As Artificial Intelligence (AI) and Machi…
Temporal Correlation of Internet Observatories and Outposts
Jeremy Kepner, Michael Jones, Daniel Andersen +26
The Internet has become a critical component of modern civilization requiring scientific exploration akin to endeavors to understand the land, sea, air, and space environments. Und…
GraphBLAS on the Edge: Anonymized High Performance Streaming of Network Traffic
Michael Jones, Jeremy Kepner, Daniel Andersen +25
Long range detection is a cornerstone of defense in many operating domains (land, sea, undersea, air, space, ..,). In the cyber domain, long range detection requires the analysis o…
Supercomputing Enabled Deployable Analytics for Disaster Response
Kaira Samuel, Jeremy Kepner, Michael Jones +17
First responders and other forward deployed essential workers can benefit from advanced analytics. Limited network access and software security requirements prevent the usage of st…
Node-Based Job Scheduling for Large Scale Simulations of Short Running Jobs
Chansup Byun, William Arcand, David Bestor +15
Diverse workloads such as interactive supercomputing, big data analysis, and large-scale AI algorithm development, requires a high-performance scheduler. This paper presents a nove…
Spatial Temporal Analysis of 40,000,000,000,000 Internet Darkspace Packets
Jeremy Kepner, Michael Jones, Daniel Andersen +24
The Internet has never been more important to our society, and understanding the behavior of the Internet is essential. The Center for Applied Internet Data Analysis (CAIDA) Telesc…
Vertical, Temporal, and Horizontal Scaling of Hierarchical Hypersparse GraphBLAS Matrices
Jeremy Kepner, Tim Davis, Chansup Byun +16
Hypersparse matrices are a powerful enabler for a variety of network, health, finance, and social applications. Hierarchical hypersparse GraphBLAS matrices enable rapid streaming u…
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…
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…
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…
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…
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…
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…