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Scout: High-Performance Heterogeneous Computing Made Simple

机译：侦察兵：高性能异构计算变得简单

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Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To achieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focus on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing high-performance by encapsulating software and hardware optimization within a compiler framework.
机译：研究人员必须常常编写自己的仿真和分析软件。在此过程中，他们同时面临计算和科学的问题。当前策略，以实现以绩效为导向的程序的产生不抽象科学的软件开发。此外，问题正变得越来越复杂，并随着许多核心和异质（CPU-GPU）架构的持续发展而迫切。为了实现高性能，科学家必须始终介绍软件和硬件。计算机科学家与研究科学家之间的共同设计可以缓解但无法解决这个问题。科学社会需要更好的工具来开发，优化和未来校对代码，使科学家们在仍然实现高计算性能的同时专注于他们的研究。 Scout是一个并行编程语言和针对异构体系结构的可扩展编译器框架。它提供了从硬件的不断转换细节中缓冲科学家所需的抽象，同时仍然通过封装编译器框架内的软件和硬件优化来实现高性能。

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