Zobrazeno 1 - 10
of 241
pro vyhledávání: '"Gadepally, Vijay"'
Autor:
Prout, Andrew, Reuther, Albert, Houle, Michael, Jones, Michael, Michaleas, Peter, Anderson, LaToya, Arcand, William, Bergeron, Bill, Bestor, David, Bonn, Alex, Burrill, Daniel, Byun, Chansup, Gadepally, Vijay, Hubbell, Matthew, Jananthan, Hayden, Luszczek, Piotr, Milechin, Lauren, Morales, Guillermo, Mullen, Julie, Rosa, Antonio, Yee, Charles, Kepner, Jeremy
HPC systems used for research run a wide variety of software and workflows. This software is often written or modified by users to meet the needs of their research projects, and rarely is built with security in mind. In this paper we explore several
Externí odkaz:
http://arxiv.org/abs/2409.10770
Autor:
Jananthan, Hayden, Jones, Michael, Arcand, William, Bestor, David, Bergeron, William, Burrill, Daniel, Buluc, Aydin, Byun, Chansup, Davis, Timothy, Gadepally, Vijay, Grant, Daniel, Houle, Michael, Hubbell, Matthew, Luszczek, Piotr, Michaleas, Peter, Milechin, Lauren, Milner, Chasen, Morales, Guillermo, Morris, Andrew, Mullen, Julie, Patel, Ritesh, Pentland, Alex, Pisharody, Sandeep, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Wachman, Gabriel, Yee, Charles, Kepner, Jeremy
The MIT/IEEE/Amazon GraphChallenge encourages community approaches to developing new solutions for analyzing graphs and sparse data derived from social media, sensor feeds, and scientific data to discover relationships between events as they unfold i
Externí odkaz:
http://arxiv.org/abs/2409.08115
Autor:
Kepner, Jeremy, Jananthan, Hayden, Jones, Michael, Arcand, William, Bestor, David, Bergeron, William, Burrill, Daniel, Buluc, Aydin, Byun, Chansup, Davis, Timothy, Gadepally, Vijay, Grant, Daniel, Houle, Michael, Hubbell, Matthew, Luszczek, Piotr, Milechin, Lauren, Milner, Chasen, Morales, Guillermo, Morris, Andrew, Mullen, Julie, Patel, Ritesh, Pentland, Alex, Pisharody, Sandeep, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Wachman, Gabriel, Yee, Charles, Michaleas, Peter
Understanding what is normal is a key aspect of protecting a domain. Other domains invest heavily in observational science to develop models of normal behavior to better detect anomalies. Recent advances in high performance graph libraries, such as t
Externí odkaz:
http://arxiv.org/abs/2409.03111
This survey offers a comprehensive overview of recent advancements in Large Language Model (LLM) serving systems, focusing on research since the year 2023. We specifically examine system-level enhancements that improve performance and efficiency with
Externí odkaz:
http://arxiv.org/abs/2407.12391
Autor:
Byun, Chansup, Mullen, Julia, Reuther, Albert, Arcand, William, Bergeron, William, Bestor, David, Burrill, Daniel, Gadepally, Vijay, Houle, Michael, Hubbell, Matthew, Jananthan, Hayden, Jones, Michael, Michaleas, Peter, Morales, Guillermo, Prout, Andrew, Rosa, Antonio, Yee, Charles, Kepner, Jeremy, Milechin, Lauren
One of the more complex tasks for researchers using HPC systems is performance monitoring and tuning of their applications. Developing a practice of continuous performance improvement, both for speed-up and efficient use of resources is essential to
Externí odkaz:
http://arxiv.org/abs/2407.01481
Autor:
Milner, Chasen, Jananthan, Hayden, Kepner, Jeremy, Gadepally, Vijay, Jones, Michael, Michaleas, Peter, Patel, Ritesh, Pisharody, Sandeep, Wachman, Gabriel, Pentland, Alex
The Internet has become a critical domain for modern society that requires ongoing efforts for its improvement and protection. Network traffic matrices are a powerful tool for understanding and analyzing networks and are broadly taught in online grap
Externí odkaz:
http://arxiv.org/abs/2404.14643
The rapid advancement of Generative Artificial Intelligence (GenAI) across diverse sectors raises significant environmental concerns, notably the carbon emissions from their cloud and high performance computing (HPC) infrastructure. This paper presen
Externí odkaz:
http://arxiv.org/abs/2403.12900
Autor:
Zhao, Dan, Samsi, Siddharth, McDonald, Joseph, Li, Baolin, Bestor, David, Jones, Michael, Tiwari, Devesh, Gadepally, Vijay
As research and deployment of AI grows, the computational burden to support and sustain its progress inevitably does too. To train or fine-tune state-of-the-art models in NLP, computer vision, etc., some form of AI hardware acceleration is virtually
Externí odkaz:
http://arxiv.org/abs/2402.18593
Autor:
Reuther, Albert, Michaleas, Peter, Jones, Michael, Gadepally, Vijay, Samsi, Siddharth, Kepner, Jeremy
This paper is an update of the survey of AI accelerators and processors from past four years, which is now called the Lincoln AI Computing Survey - LAICS (pronounced "lace"). As in past years, this paper collects and summarizes the current commercial
Externí odkaz:
http://arxiv.org/abs/2310.09145