Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Bestor, David"'
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:
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:
Jananthan, Hayden, Kepner, Jeremy, Jones, Michael, Arcand, William, Bestor, David, Bergeron, William, Byun, Chansup, Davis, Timothy, Gadepally, Vijay, Grant, Daniel, Houle, Michael, Hubbell, Matthew, Klein, Anna, Milechin, Lauren, Morales, Guillermo, Morris, Andrew, Mullen, Julie, Patel, Ritesh, Pentland, Alex, Pisharody, Sandeep, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Siddharth, Trigg, Tyler, Wachman, Gabriel, Yee, Charles, Michaleas, Peter
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 their potential geometric interpretations. Analyses of large scale network
Externí odkaz:
http://arxiv.org/abs/2310.00522
Autor:
Byun, Chansup, Arcand, William, Bestor, David, Bergeron, Bill, Gadepally, Vijay, Houle, Michael, Hubbell, Matthew, Jananthan, Hayden, Jones, Michael, Klein, Anna, Michaleas, Peter, Milechin, Lauren, Morales, Guillermo, Mullen, Julie, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Siddharth, Yee, Charles, Kepner, Jeremy
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 (PGAS) on top of a simple file-based messaging library (PythonMPI) in
Externí odkaz:
http://arxiv.org/abs/2309.03931
Autor:
Jones, Michael, Kepner, Jeremy, Prout, Andrew, Davis, Timothy, Arcand, William, Bestor, David, Bergeron, William, Byun, Chansup, Gadepally, Vijay, Houle, Micheal, Hubbell, Matthew, Jananthan, Hayden, Klein, Anna, Milechin, Lauren, Morales, Guillermo, Mullen, Julie, Patel, Ritesh, Pisharody, Sandeep, Reuther, Albert, Rosa, Antonio, Samsi, Siddharth, Yee, Charles, Michaleas, Peter
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, performance, and compression capabilities of GraphBLAS (graphblas.org) hyperspa
Externí odkaz:
http://arxiv.org/abs/2309.02464
Autor:
Kepner, Jeremy, Jones, Michael, Dykstra, Phil, Byun, Chansup, Davis, Timothy, Jananthan, Hayden, Arcand, William, Bestor, David, Bergeron, William, Gadepally, Vijay, Houle, Micheal, Hubbell, Matthew, Klein, Anna, Milechin, Lauren, Morales, Guillermo, Mullen, Julie, Patel, Ritesh, Pentland, Alex, Pisharody, Sandeep, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Siddharth, Trigg, Tyler, Yee, Charles, Michaleas, Peter
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 cyberspace. Deployment of the necessary network sensors requires care
Externí odkaz:
http://arxiv.org/abs/2309.01806
Autor:
Zhao, Dan, Frey, Nathan C., McDonald, Joseph, Hubbell, Matthew, Bestor, David, Jones, Michael, Prout, Andrew, Gadepally, Vijay, Samsi, Siddharth
Publikováno v:
D. Zhao et al., "A Green(er) World for A.I.," 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Lyon, France, 2022, pp. 742-750
As research and practice in artificial intelligence (A.I.) grow in leaps and bounds, the resources necessary to sustain and support their operations also grow at an increasing pace. While innovations and applications from A.I. have brought significan
Externí odkaz:
http://arxiv.org/abs/2301.11581
Autor:
Trigg, Tyler, Meiners, Chad, Pisharody, Sandeep, Jananthan, Hayden, Jones, Michael, Michaleas, Adam, Davis, Timothy, Welch, Erik, Arcand, William, Bestor, David, Bergeron, William, Byun, Chansup, Gadepally, Vijay, Houle, Micheal, Hubbell, Matthew, Klein, Anna, Michaleas, Peter, Milechin, Lauren, Mullen, Julie, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Siddharth, Stetson, Doug, Yee, Charles, Kepner, Jeremy
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 flows (netflows) that contain the start time, stop time, source, dest
Externí odkaz:
http://arxiv.org/abs/2209.05725
Autor:
Weiss, Matthew L., McDonald, Joseph, Bestor, David, Yee, Charles, Edelman, Daniel, Jones, Michael, Prout, Andrew, Bowne, Andrew, McEvoy, Lindsey, Gadepally, Vijay, Samsi, Siddharth
In this paper we address the application of pre-processing techniques to multi-channel time series data with varying lengths, which we refer to as the alignment problem, for downstream machine learning. The misalignment of multi-channel time series d
Externí odkaz:
http://arxiv.org/abs/2209.05300
Autor:
Jananthan, Hayden, Milechin, Lauren, Jones, Michael, Arcand, William, Bergeron, William, Bestor, David, Byun, Chansup, Houle, Michael, Hubbell, Matthew, Gadepally, Vijay, Klein, Anna, Michaleas, Peter, Morales, Guillermo, Mullen, Julie, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Siddharth, Yee, Charles, Kepner, Jeremy
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 Dynamic Distributed Dimensional Data Model (D4M) offers a highly compo
Externí odkaz:
http://arxiv.org/abs/2209.00602