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Journal article
SPIRAL: Extreme Performance Portability
Proceedings of the IEEE, v 106(11), pp 1935-1968
01 Nov 2018
Abstract
In this paper, we address the question of how to automatically map computational kernels to highly efficient code for a wide range of computing platforms and establish the correctness of the synthesized code. More specifically, we focus on two fundamental problems that software developers are faced with: performance portability across the ever-changing landscape of parallel platforms and correctness guarantees for sophisticated floating-point code. The problem is approached as follows: We develop a formal framework to capture computational algorithms, computing platforms, and program transformations of interest, using a unifying mathematical formalism we call operator language (OL). Then we cast the problem of synthesizing highly optimized computational kernels for a given machine as a strongly constrained optimization problem that is solved by search and a multistage rewriting system. Since all rewrite steps are semantics preserving, our approach establishes equivalence between the kernel specification and the synthesized program. This approach is implemented in the SPIRAL system, and we demonstrate it with a selection of computational kernels from the signal and image processing domain, software-defined radio, and robotic vehicle control. Our target platforms range from mobile devices, desktops, and server multicore processors to large-scale high-performance and supercomputing systems, and we demonstrate performance comparable to expertly hand-tuned code across kernels and platforms.
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Details
- Title
- SPIRAL: Extreme Performance Portability
- Creators
- Franz Franchetti - Carnegie Mellon UniversityTze Meng Low - Carnegie Mellon UniversityDoru Thom Popovici - Carnegie Mellon UniversityRichard M. Veras - Louisiana State UniversityDaniele G. Spampinato - Carnegie Mellon UniversityJeremy R. Johnson - Drexel UniversityMarkus Puschel - ETH ZurichJames C. Hoe - Carnegie Mellon UniversityJose M. F. Moura - Carnegie Mellon University
- Publication Details
- Proceedings of the IEEE, v 106(11), pp 1935-1968
- Publisher
- IEEE
- Number of pages
- 34
- Grant note
- 0325687; 0702386; 0931987 / National Science Foundation (NSF); National Research Foundation of Korea Mercury DM17-0413 / Carnegie Mellon University FA8750-12-2-0291; FA8750-16-2-0033; HR0011-13-2-0007 / DARPA; United States Department of Defense; Defense Advanced Research Projects Agency (DARPA) Intel; Intel Corporation Nvidia N000141110112 / U.S. Office of Naval Research (ONR); Office of Naval Research FA8702-15-D-0002 / Department of Defense; United States Department of Defense NBCH1050009 / DOI W911NF0710416 / ARO
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000448616200007
- Scopus ID
- 2-s2.0-85055816845
- Other Identifier
- 991019168558004721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Electrical & Electronic