GPU algorithms for Efficient Exascale Discretizations

Date

2021-12-01

Author

Abdelfattah, Ahmad
Barra, Valeria
Beams, Natalie
Bleile, Ryan
Brown, Jed
Camier, Jean-Sylvain
Carson, Robert
Chalmers, Noel
Dobrev, Veselin
Dudouit, Yohann
Fischer, Paul
Karakuş, Ali
Kerkemeier, Stefan
Kolev, Tzanio
Lan, Yu-Hsiang
Merzari, Elia
Min, Misun
Phillips, Malachi
Rathnayake, Thilina
Rieben, Robert
Stitt, Thomas
Tomboulides, Ananias
Tomov, Stanimire
Tomov, Vladimir
Vargas, Arturo
Warburton, Tim
Weiss, Kenneth

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

179
views

0
downloads

In this paper we describe the research and development activities in the Center for Efficient Exascale Discretization within the US Exascale Computing Project, targeting state-of-the-art high-order finite-element algorithms for high-order applications on GPU-accelerated platforms. We discuss the GPU developments in several components of the CEED software stack, including the libCEED, MAGMA, MFEM, libParanumal, and Nek projects. We report performance and capability improvements in several CEED-enabled applications on both NVIDIA and AMD GPU systems.

Subject Keywords

High-performance computing, GPU acceleration, High-order discretizations

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85115934300&origin=inward
https://hdl.handle.net/11511/93985

Journal

Parallel Computing

DOI

https://doi.org/10.1016/j.parco.2021.102841

Collections

Department of Mechanical Engineering, Article

Suggestions

OpenMETU
Core

CLOUDGEN: Workload generation for the evaluation of cloud computing systems CLOUDGEN: Bulut Bilişim Sistemlerinin Başarim Deǧerlendirmesi icin Iş Yuku Uretimi Koltuk, Furkan; Yazar, Alper; Schmidt, Şenan Ece (2019-04-01) In this paper, we propose CLOUDGEN workflow that produces synthetic workloads for Infrastructure and Platform as a Service for the evaluation of resource management approaches in cloud computing systems. To this end, CLOUDGEN systematically processes and clusters records in a given workload trace and fits distributions for different workload parameters within the clusters. Different than the previous work, clustering is carried out to produce different virtual machine types for achieving models that are sui...
GMDH-type neural network algorithms for short term forecasting Dağ, Osman; Yozgatlıgil, Ceylan; Department of Statistics (2015) Group Method of Data Handling (GMDH) - type neural network algorithms are the heuristic self-organization method for modelling the complex systems. GMDH algorithms are utilized for the variety of purposes, which are identification of physical laws, extrapolation of physical fields, pattern recognition, clustering, approximation of multidimensional processes, forecasting without models and so on. In this study, GMDH - type neural network algorithms were applied to make forecasts for time series data sets. We...
Electromagnetic Target Classification using time frequency analysis and neural networks Sayan, Gönül; Leblebicioğlu, Mehmet Kemal (Wiley, 1999-04-01) This paper demonstrates the feasibility and advantages of using a self-organizing map (SOM)-type neural network classifier for electromagnetic target recognition. The classifier is supported by a novel feature extraction unit in which the Wigner distribution (WD), a time-frequency representation, is utilized for the extraction of natural-resonance-related energy feature vectors from scattered fields. The proposed target classification technique is tested for a set of canonical targets, displaying an excelle...
ACCLOUD-MAN - Power efficient resource allocation for heterogeneous clouds ACCLOUD-MAN - Heterojen bulutlarda güç etkin kaynak atamasi Ekici, Nazim Umut; Schmidt, Klaus Werner; Yazar, Alper; Schmidt, Şenan Ece (2019-04-01) In this paper we propose ACCLOUD-MAN, a novel resource manager for heterogeneous cloud data centers. In heterogeneous clouds a user request can be satisfied with more than one physical resource alternative. Resource manager must decide which resource alternative will be chosen, along with the decision of the server the request will be assigned to. ACCLOUD-MAN's resource management objective is to reduce the power consumption of the cloud. Manager is modeled as an Integer Linear Problem and is implemented on...
High efficiency combined - cycle gas polygenerator for ecological local generation (HEGEL) Pınarcıoğlu, Mehmet Melih(2009-4-30) Objective is to develop, demonstrate and assess an innovative, high efficiency concept of micro-cogeneration system applied to a real demand site under real operating conditions. The application concept is based on a combined cycle architecture (Combi system) constituted by two integrated cogenerators powered by different prime movers: an innovative reciprocating engine cogenerator and a Rankine engine system (bottoming cycle) operated on the exhaust gases of the reciprocating engine. The location will b...

Citation Formats

A. Abdelfattah et al., “GPU algorithms for Efficient Exascale Discretizations,” Parallel Computing, vol. 108, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85115934300&origin=inward.