PEPPHER: Efficient and Productive Usage of Hybrid Computing Systems
AUGONNET, Cédric
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
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Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
Language
en
Article de revue
This item was published in
IEEE Micro. 2011, vol. 31, n° 5, p. 28-41
Institute of Electrical and Electronics Engineers
English Abstract
The 3-year European FP7 project PEPPHER addresses efficient utilization and usage of hybrid (heterogeneous) computer systems consisting of multi-core CPUs with GPU-type accelerators. PEPPHER is concerned with two major ...Read more >
The 3-year European FP7 project PEPPHER addresses efficient utilization and usage of hybrid (heterogeneous) computer systems consisting of multi-core CPUs with GPU-type accelerators. PEPPHER is concerned with two major aspects: programmability and efficiency on given heterogeneous systems, and code and performance portability between different heterogeneous systems. The PEPPHER approach is pluralistic and parallelization agnostic, aiming to support different parallel languages and frameworks at different levels of parallelism. The central idea of PEPPHER is to maintain multiple, tailored implementation variants of performance-critical components of the application and schedule these efficiently either dynamically or statically across the available CPU and GPU resources. Implementation variants are supplied incrementally by hand, by compilation, by component composition, by auto-tuning, or taken from expert-written, adaptive libraries. This paper outlines the PEPPHER performance aware component model, its means for performance prediction, the PEPPHER run-time system, and other major aspects of the project concerned with algorithm and data structure support, compilation, and hardware feedback. A larger example demonstrating performance portability with the PEPPHER approach across hybrid systems with one to four GPUs is discussed: each GPU that is added to the system brings a linear performance increase, and performance aware scheduling provides for more efficient utilization of the combined CPU-GPU resources.Read less <
European Project
Performance Portability and Programmability for Heterogeneous Many-core Architectures
Origin
Hal imported