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DOE OSTI · 1733300

Hardware Evaluation: Abstract Machine Models and Proxy Architectures for Exascale Computing

Bair, Ray·Chien, Andrew·Cook, Jeanine·Donofrio, Dave·Grider, Gary·Kuehn, Jeff·Moore, Shirley·Shalf, John·Vetter, Jeff
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Abstract

The strategic and economic impacts of high performance computing (HPC) systems, over the last several decades, have enabled dramatic improvements in manufacturing, design, development, and research, across almost every sector of the U.S. economy, including genetic analysis for agriculture and medicine, oil exploration, electronics, aircraft, and automotive design, and of course national defense technologies. HPC has repeatedly compounded reductions in time-to-solution and time-to-market in each of these areas. In recognition of these strategic and economic impacts, the Department of Energy (DOE) created the Exascale Computing Project (ECP) as a broad-based technology project focusing on simultaneously co-evolving high-performance computing architecture, system software, and application software. While many details of the exascale architectures are undefined, communicating the form and direction of this co-evolution of advances, in each of these three components, across the project, presents a need for a common language through which these advances can be shared. In this document we present a series of abstract representations designed to allow application developers to focus on the aspects of the machine that are important or relevant to performance and code structure. These abstract machine models (AMMs) describe the proposed architectures at the component and system level and are intended as communication aids between application developers and hardware architects during the co-design process. In addition to providing a common language for communication, the constraints of protecting the intellectual property of ECP’s vendor partners requires that the architectural advances be presented in an abstract sense, rather than exposing the specifics of an individual vendor’s designs, while still providing enough detail such that application developers will be able to reason about the performance trade-offs in the design space of their applications.

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Bair, Ray, Chien, Andrew, Cook, Jeanine, Donofrio, Dave, Grider, Gary, Kuehn, Jeff, Moore, Shirley, Shalf, John, Vetter, Jeff. 2018-02-01. Hardware Evaluation: Abstract Machine Models and Proxy Architectures for Exascale Computing. https://doi.org/10.2172/1733300

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