Exascale Monte Carlo R&D
Description/Abstract
Overview of this presentation is (1) Exascale computing - different technologies, getting there; (2) high-performance proof-of-concept MCMini - features and results; and (3) OpenCL toolkit - Oatmeal (OpenCL Automatic Memory Allocation Library) - purpose and features. Despite driver issues, OpenCL seems like a good, hardware agnostic tool. MCMini demonstrates the possibility for GPGPU-based Monte Carlo methods - it shows great scaling for HPC application and algorithmic equivalence. Oatmeal provides a flexible framework to aid in the development of scientific OpenCL codes.
| DOI | 10.2172/1047104 |
|---|---|
| Creator/Author: | Marcus, Ryan C. [Los Alamos National Laboratory] |
| Publication Date: | 2012 Jul 24 |
| OSTI Identifier: | OSTI ID: 1047104 |
| Report Number(s): | LA-UR-12-23349 |
| DOE Contract Number: | AC52-06NA25396 |
| DOI: | 10.2172/1047104 |
| Other Number(s): | TRN: US201216%%347 |
| Resource Type: | Technical Report |
| Research Org: | Los Alamos National Laboratory (LANL) |
| Sponsoring Org: | DOE/LANL |
| Subject: | 97 MATHEMATICAL METHODS AND COMPUTING; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; MONTE CARLO METHOD; COMPUTERS; COMPUTER CODES; PROGRAMMING |
| Country of Publication: | United States |
| Language: | English |
| Update Date: | 2012 Dec 05 |
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