Name
Abstract | ||
|---|---|---|
To achieve exascale computing, fundamental hardware architectures must change. This will significantly impact scientific applications that run on current high performance computing (HPC) systems, many of which codify years of scientific domain knowledge and refinements for contemporary computer systems. To adapt to exascale architectures, developers must be able to reason about new hardware and determine what programming models and algorithms will provide the best blend of performance and energy efficiency in the future. An abstract machine model is designed to expose to the application developers and system software only the aspects of the machine that are important or relevant to performance and code structure. These models are intended as communication aids between application developers and hardware architects during the co-design process. A proxy architecture is a parameterized version of an abstract machine model, with parameters added to elucidate potential speeds and capacities of key hardware components. These more detailed architectural models enable discussion among the developers of analytic models and simulators and computer hardware architects and they allow for application performance analysis, system software development, and hardware optimization opportunities. In this paper, we present a set of abstract machine models and show how they might be used to help software developers prepare for exascale. We then apply parameters to one of these models to demonstrate how a proxy architecture can enable a more concrete exploration of how well application codes map onto future architectures. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/Co-HPC.2014.4 | Co-HPC@SC |
Keywords | Field | DocType |
optimisation,parallel processing,power aware computing,HPC,abstract machine model,application codes,application performance analysis,code structure,codesign process,computer hardware architects,contemporary computer systems,energy efficiency,exascale computing,fundamental hardware architectures,hardware architects,hardware optimization opportunities,high performance computing systems,programming models,proxy architecture,proxy architectures,scientific applications,system software,system software development | System software,Exascale computing,Computer architecture,Programming paradigm,Hardware compatibility list,Supercomputer,Computer science,Parallel computing,Software,Abstract machine,Hardware architecture,Distributed computing | Conference |
Citations | PageRank | References |
23 | 0.80 | 15 |
Authors | ||
18 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. A. Ang | 1 | 23 | 0.80 |
| Richard F. Barrett | 2 | 286 | 22.94 |
| R. E. Benner | 3 | 23 | 0.80 |
| Burke, D. | 4 | 23 | 0.80 |
| Keith C. C. Chan | 5 | 983 | 108.02 |
| J. Cook | 6 | 23 | 0.80 |
| David Donofrio | 7 | 133 | 16.02 |
| S. D. Hammond | 8 | 198 | 19.05 |
| Karl S. Hemmert | 9 | 23 | 0.80 |
| S. M. Kelly | 10 | 23 | 0.80 |
| H. Le | 11 | 23 | 0.80 |
| V. J. Leung | 12 | 23 | 0.80 |
| David R. Resnick | 13 | 25 | 1.51 |
| Arun Rodrigues | 14 | 172 | 15.68 |
| John Shalf | 15 | 2353 | 211.77 |
| Dylan T. Stark | 16 | 58 | 2.82 |
| Didem Unat | 17 | 189 | 17.71 |
| Nicholas J. Wright | 18 | 408 | 27.79 |