Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Mohammed Tanash"'
Publikováno v:
PEARC
In this paper, we present a novel methodology for predicting job resources (memory and time) for submitted jobs on HPC systems. Our methodology based on historical jobs data (saccount data) provided from the Slurm workload manager using supervised ma
Autor:
Calvin Frye, Daniel Voss, Sandra Gesing, Dirk Colbry, Henry Neeman, Patrick J. Clemins, Anna Klimaszewski-Patterson, Mohammed Tanash, Todd Price, Dana Brunson, Anchalee Phataralaoha, Lizanne DeStefano, Lorna Rivera, Hussein Al-Azzawi, Joshua V. Gyllinsky
Publikováno v:
PEARC
Cyberinfrastructure (CI) Facilitation amplifies the productivity of researchers engaged in computing-intensive and data-intensive investigations. CI Facilitators help researchers to adapt their workflows to CI resources, and teaches these researchers
Autor:
David L. Akin, Sandra Gesing, Dirk Colbry, Mohammed Tanash, Claire Mizumoto, Anna Klimaszewski-Patterson, Henry Neeman, Kevin Brandt, Anita Schwartz, Daniel Voss, Joy A. Pine-Thomas, Dana Brunson, Jamene Brooks Kieffer, Hussein Al-Azzawi, Horst Severini
Publikováno v:
PEARC
Cyberinfrastructure (CI) Facilitation is the process of helping researchers to use research computing systems and services to advance their computing/data-intensive research goals. The growing need for CI Facilitation isn’t being met by traditional
Autor:
Hussein Al-Azzawi, Jeff T. Falgout, Daniel Voss, Sandra Gesing, Scott Yockel, Joshua V. Gyllinsky, Jason L. Simms, Christopher S. Simmons, Dirk Colbry, Dana Brunson, Jason Wells, Henry Neeman, Mohammed Tanash, William Burke, James W. Ferguson
Publikováno v:
PEARC
Cyberinfrastructure (CI) Facilitation is the process of helping researchers to use research computing systems and services to advance their computing-intensive/data-intensive research goals. The growing need for CI Facilitation isn't being met by tra
Autor:
Adedolapo Okanlawon, Huichen Yang, Daniel Andresen, Mohammed Tanash, William H. Hsu, Brandon Dunn
Publikováno v:
PEARC19 (2019)
PEARC
PEARC
High-Performance Computing (HPC) systems are resources utilized for data capture, sharing, and analysis. The majority of our HPC users come from other disciplines than Computer Science. HPC users including computer scientists have difficulties and do
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8821ddc7d9e88b1f4e1fea9b79d68b5a
https://europepmc.org/articles/PMC8932944/
https://europepmc.org/articles/PMC8932944/
Publikováno v:
CLUSTER
In this paper, we present a methodology for modeling the expected runtime of a job based on historical application data and data from the job itself. This estimation model is useful for both for HPC users and administrators as a metric to compare the
Publikováno v:
IPDPS Workshops
Exposing the runtime behavior of long running, resource-burning scientific applications on HPC platforms is a must if the platforms are going to be used efficiently and wisely. This paper presents a small work in progress that aims to automatically i
Autor:
Adedolapo O; Department of Computer Science, Kansas State University, Manhattan, Kansas, USA., Huichen Y; Department of Computer Science, Kansas State University, Manhattan, Kansas, USA., Avishek B; Department of Computer Science, Kansas State University, Manhattan, Kansas, USA., William H; Department of Computer Science, Kansas State University, Manhattan, Kansas, USA., Dan A; Department of Computer Science, Kansas State University, Manhattan, Kansas, USA., Mohammed T; Department of Computer Science, Kansas State University, Manhattan, Kansas, USA.
Publikováno v:
Proceedings. International Conference on Computational Science and Computational Intelligence [Proc (Int Conf Comput Sci Comput Intell)] 2020 Dec; Vol. 2020, pp. 1231-1236.