Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Huck, Kevin A."'
Autor:
Williams, Jeremy J., Costea, Stefan, Malony, Allen D., Tskhakaya, David, Kos, Leon, Podolnik, Ales, Hromadka, Jakub, Huck, Kevin, Laure, Erwin, Markidis, Stefano
Particle-in-Cell Monte Carlo simulations on large-scale systems play a fundamental role in understanding the complexities of plasma dynamics in fusion devices. Efficient handling and analysis of vast datasets are essential for advancing these simulat
Externí odkaz:
http://arxiv.org/abs/2406.19058
Autor:
Boito, Francieli, Brandt, Jim, Cardellini, Valeria, Carns, Philip, Ciorba, Florina M., Egan, Hilary, Eleliemy, Ahmed, Gentile, Ann, Gruber, Thomas, Hanson, Jeff, Haus, Utz-Uwe, Huck, Kevin, Ilsche, Thomas, Jakobsche, Thomas, Jones, Terry, Karlsson, Sven, Mueen, Abdullah, Ott, Michael, Patki, Tapasya, Peng, Ivy, Raghavan, Krishnan, Simms, Stephen, Shoga, Kathleen, Showerman, Michael, Tiwari, Devesh, Wilde, Torsten, Yamamoto, Keiji
Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of system
Externí odkaz:
http://arxiv.org/abs/2401.16971
This paper presents a approach for measuring the time spent by HPC applications in the operating system's kernel. We use the SystemTap interface to insert timers before and after system calls, and take advantage of its stability to design a tool that
Externí odkaz:
http://arxiv.org/abs/2304.11205
Autor:
Diehl, Patrick, Daiß, Gregor, Huck, Kevin, Marcello, Dominic, Shiber, Sagiv, Kaiser, Hartmut, Pflüger, Dirk
The increasing availability of machines relying on non-GPU architectures, such as ARM A64FX in high-performance computing, provides a set of interesting challenges to application developers. In addition to requiring code portability across different
Externí odkaz:
http://arxiv.org/abs/2304.11002
Autor:
Diehl, Patrick, Daiss, Gregor, Huck, Kevin, Marcello, Dominic, Shiber, Sagiv, Kaiser, Hartmut, Frank, Juhan, Clayton, Geoffrey C., Pflueger, Dirk
Benchmarking and comparing performance of a scientific simulation across hardware platforms is a complex task. When the simulation in question is constructed with an asynchronous, many-task (AMT) runtime offloading work to GPUs, the task becomes even
Externí odkaz:
http://arxiv.org/abs/2210.06437
Modern accelerators use hierarchical parallel programming models that enable massive multithreading within a processing element (PE), with multiple PEs per device driven by traditional processes. Batching is a technique for exposing PE-level parallel
Externí odkaz:
http://arxiv.org/abs/2209.03228
Autor:
Sakin, Sayef Azad, Bigelow, Alex, Tohid, R., Scully-Allison, Connor, Scheidegger, Carlos, Brandt, Steven R., Taylor, Christopher, Huck, Kevin A., Kaiser, Hartmut, Isaacs, Katherine E.
Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings i
Externí odkaz:
http://arxiv.org/abs/2208.00109
Autor:
Diehl, Patrick, Daiß, Gregor, Marcello, Dominic, Huck, Kevin, Shiber, Sagiv, Kaiser, Hartmut, Frank, Juhan, Pflüger, Dirk
Octo-Tiger is a code for modeling three-dimensional self-gravitating astrophysical fluids. It was particularly designed for the study of dynamical mass transfer between interacting binary stars. Octo-Tiger is parallelized for distributed systems usin
Externí odkaz:
http://arxiv.org/abs/2107.10987
Autor:
Wei, Weile, D'Azevedo, Eduardo, Huck, Kevin, Chatterjee, Arghya, Hernandez, Oscar, Kaiser, Hartmut
Scientific applications that run on leadership computing facilities often face the challenge of being unable to fit leading science cases onto accelerator devices due to memory constraints (memory-bound applications). In this work, the authors studie
Externí odkaz:
http://arxiv.org/abs/2105.00027
Autor:
Diehl, Patrick, Marcello, Dominic, Amini, Parsa, Kaiser, Hartmut, Shiber, Sagiv, Clayton, Geoffrey C., Frank, Juhan, Daiß, Gregor, Pflüger, Dirk, Eder, David, Koniges, Alice, Huck, Kevin
Analyzing performance within asynchronous many-task-based runtime systems is challenging because millions of tasks are launched concurrently. Especially for long-term runs the amount of data collected becomes overwhelming. We study HPX and its perfor
Externí odkaz:
http://arxiv.org/abs/2102.00223