Siddharth Samsi

research

∙ 09/07/2023

pPython Performance Study

pPython seeks to provide a parallel capability that provides good speed-...

0 Chansup Byun, et al. ∙

research

∙ 09/04/2023

Focusing and Calibration of Large Scale Network Sensors using GraphBLAS Anonymized Hypersparse Matrices

Defending community-owned cyber space requires community-based efforts. ...

0 Jeremy Kepner, et al. ∙

research

∙ 09/04/2023

Deployment of Real-Time Network Traffic Analysis using GraphBLAS Hypersparse Matrices and D4M Associative Arrays

Matrix/array analysis of networks can provide significant insight into t...

0 Michael Jones, et al. ∙

research

∙ 06/22/2023

Sustainable HPC: Modeling, Characterization, and Implications of Carbon Footprint in Modern HPC Systems

The rapid growth in demand for HPC systems has led to a rise in energy c...

0 Baolin Li, et al. ∙

research

∙ 04/19/2023

Green Carbon Footprint for Model Inference Serving via Exploiting Mixed-Quality Models and GPU Partitioning

This paper presents a solution to the challenge of mitigating carbon emi...

0 Baolin Li, et al. ∙

research

∙ 01/27/2023

A Green(er) World for A.I

As research and practice in artificial intelligence (A.I.) grow in leaps...

0 Dan Zhao, et al. ∙

research

∙ 10/12/2022

Building Heterogeneous Cloud System for Machine Learning Inference

Online inference is becoming a key service product for many businesses, ...

0 Baolin Li, et al. ∙

research

∙ 10/08/2022

AI and ML Accelerator Survey and Trends

This paper updates the survey of AI accelerators and processors from pas...

0 Albert Reuther, et al. ∙

research

∙ 09/13/2022

Hypersparse Network Flow Analysis of Packets with GraphBLAS

Internet analysis is a major challenge due to the volume and rate of net...

0 Tyler Trigg, et al. ∙

research

∙ 09/12/2022

An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning

In this paper we address the application of pre-processing techniques to...

0 Matthew L Weiss, et al. ∙

research

∙ 09/01/2022

Python Implementation of the Dynamic Distributed Dimensional Data Model

Python has become a standard scientific computing language with fast-gro...

0 Hayden Jananthan, et al. ∙

research

∙ 08/31/2022

pPython for Parallel Python Programming

pPython seeks to provide a parallel capability that provides good speed-...

0 Chansup Byun, et al. ∙

research

∙ 07/14/2022

Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government ...

5 Vijay Gadepally, et al. ∙

research

∙ 05/19/2022

Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models

The energy requirements of current natural language processing models co...

0 Joseph McDonald, et al. ∙

research

∙ 04/12/2022

The MIT Supercloud Workload Classification Challenge

High-Performance Computing (HPC) centers and cloud providers support an ...

0 Benny J. Tang, et al. ∙

research

∙ 03/25/2022

GraphBLAS on the Edge: Anonymized High Performance Streaming of Network Traffic

Long range detection is a cornerstone of defense in many operating domai...

0 Michael Jones, et al. ∙

research

∙ 03/19/2022

Temporal Correlation of Internet Observatories and Outposts

The Internet has become a critical component of modern civilization requ...

0 Jeremy Kepner, et al. ∙

research

∙ 01/28/2022

Benchmarking Resource Usage for Efficient Distributed Deep Learning

Deep learning (DL) workflows demand an ever-increasing budget of compute...

0 Nathan C. Frey, et al. ∙

research

∙ 12/09/2021

Bringing Atomistic Deep Learning to Prime Time

Artificial intelligence has not yet revolutionized the design of materia...

21 Nathan C. Frey, et al. ∙

research

∙ 12/06/2021

Scalable Geometric Deep Learning on Molecular Graphs

Deep learning in molecular and materials sciences is limited by the lack...

3 Nathan C. Frey, et al. ∙

research

∙ 11/13/2021

The Pseudo Projection Operator: Applications of Deep Learning to Projection Based Filtering in Non-Trivial Frequency Regimes

Traditional frequency based projection filters, or projection operators ...

0 Matthew L Weiss, et al. ∙

research

∙ 09/18/2021

AI Accelerator Survey and Trends

Over the past several years, new machine learning accelerators were bein...

0 Albert Reuther, et al. ∙

research

∙ 09/09/2021

3D Real-Time Supercomputer Monitoring

Supercomputers are complex systems producing vast quantities of performa...

0 Bill Bergeron, et al. ∙

research

∙ 08/25/2021

Node-Based Job Scheduling for Large Scale Simulations of Short Running Jobs

Diverse workloads such as interactive supercomputing, big data analysis,...

0 Chansup Byun, et al. ∙

research

∙ 08/15/2021

Spatial Temporal Analysis of 40,000,000,000,000 Internet Darkspace Packets

The Internet has never been more important to our society, and understan...

0 Jeremy Kepner, et al. ∙

research

∙ 08/15/2021

Vertical, Temporal, and Horizontal Scaling of Hierarchical Hypersparse GraphBLAS Matrices

Hypersparse matrices are a powerful enabler for a variety of network, he...

0 Jeremy Kepner, et al. ∙

research

∙ 08/04/2021

The MIT Supercloud Dataset

Artificial intelligence (AI) and Machine learning (ML) workloads are an ...

0 Siddharth Samsi, et al. ∙

research

∙ 09/01/2020

Survey of Machine Learning Accelerators

New machine learning accelerators are being announced and released each ...

0 Albert Reuther, et al. ∙

research

∙ 08/20/2020

Accuracy and Performance Comparison of Video Action Recognition Approaches

Over the past few years, there has been significant interest in video ac...

6 Matthew Hutchinson, et al. ∙

research

∙ 08/18/2020

Compute, Time and Energy Characterization of Encoder-Decoder Networks with Automatic Mixed Precision Training

Deep neural networks have shown great success in many diverse fields. Th...

0 Siddharth Samsi, et al. ∙

research

∙ 08/18/2020

Benchmarking network fabrics for data distributed training of deep neural networks

Artificial Intelligence/Machine Learning applications require the traini...

0 Siddharth Samsi, et al. ∙

research

∙ 08/05/2020

Best of Both Worlds: High Performance Interactive and Batch Launching

Rapid launch of thousands of jobs is essential for effective interactive...

0 Chansup Byun, et al. ∙

research

∙ 08/01/2020

Multi-Temporal Analysis and Scaling Relations of 100,000,000,000 Network Packets

Our society has never been more dependent on computer networks. Effectiv...

0 Jeremy Kepner, et al. ∙

research

∙ 07/14/2020

Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks via Nonlinear Multigrid

A Multigrid Full Approximation Storage algorithm for solving Deep Residu...

3 Andrew C. Kirby, et al. ∙

research

∙ 03/18/2020

GraphChallenge.org Triangle Counting Performance

The rise of graph analytic systems has created a need for new ways to me...

0 Siddharth Samsi, et al. ∙

research

∙ 01/20/2020

75,000,000,000 Streaming Inserts/Second Using Hierarchical Hypersparse GraphBLAS Matrices

The SuiteSparse GraphBLAS C-library implements high performance hyperspa...

0 Jeremy Kepner, et al. ∙

research

∙ 01/18/2020

AI Data Wrangling with Associative Arrays

The AI revolution is data driven. AI "data wrangling" is the process by ...

0 Jeremy Kepner, et al. ∙

research

∙ 09/03/2019

Large Scale Parallelization Using File-Based Communications

In this paper, we present a novel and new file-based communication archi...

0 Chansup Byun, et al. ∙

research

∙ 08/29/2019

Survey and Benchmarking of Machine Learning Accelerators

Advances in multicore processors and accelerators have opened the flood ...

0 Albert Reuther, et al. ∙

research

∙ 08/29/2019

TapirXLA: Embedding Fork-Join Parallelism into the XLA Compiler in TensorFlow Using Tapir

This work introduces TapirXLA, a replacement for TensorFlow's XLA compil...

0 Tao B. Schardl, et al. ∙

research

∙ 08/28/2019

Distributed Deep Learning for Precipitation Nowcasting

Effective training of Deep Neural Networks requires massive amounts of d...

28 Siddharth Samsi, et al. ∙

research

∙ 08/20/2019

Securing HPC using Federated Authentication

Federated authentication can drastically reduce the overhead of basic ac...

0 Andrew Prout, et al. ∙

research

∙ 08/16/2019

Large Scale Organization and Inference of an Imagery Dataset for Public Safety

Video applications and analytics are routinely projected as a stressing ...

0 Jeffrey Liu, et al. ∙

research

∙ 07/06/2019

Optimizing Xeon Phi for Interactive Data Analysis

The Intel Xeon Phi manycore processor is designed to provide high perfor...

0 Chansup Byun, et al. ∙

research

∙ 07/06/2019

Streaming 1.9 Billion Hypersparse Network Updates per Second with D4M

The Dynamic Distributed Dimensional Data Model (D4M) library implements ...

0 Jeremy Kepner, et al. ∙

research

∙ 05/08/2019

AI Enabling Technologies: A Survey

Artificial Intelligence (AI) has the opportunity to revolutionize the wa...

0 Vijay Gadepally, et al. ∙

research

∙ 03/05/2019

Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers

For decades, the use of HPC systems was limited to those in the physical...

0 Julia Mullen, et al. ∙

research

∙ 02/03/2019

A Billion Updates per Second Using 30,000 Hierarchical In-Memory D4M Databases

Analyzing large scale networks requires high performance streaming updat...

0 Jeremy Kepner, et al. ∙

research

∙ 08/25/2018

Hyperscaling Internet Graph Analysis with D4M on the MIT SuperCloud

Detecting anomalous behavior in network traffic is a major challenge due...

0 Vijay Gadepally, et al. ∙

research

∙ 08/13/2018

Interactive Launch of 16,000 Microsoft Windows Instances on a Supercomputer

Simulation, machine learning, and data analysis require a wide range of ...

0 Michael Jones, et al. ∙

Siddharth Samsi

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