Compilers, Tools and Languages for Scientists

计算和编程正成为科学家工作中越来越重要的方面。然而，科学家面临着许多挑战，并不一定拥有适当的语言、编译器和软件工具来高效、安全地实现他们的目标。《自然》杂志2010年发表的一篇题为《为什么科学编程不计算》的文章描述了编程的日益重要，科学家面临的挑战，以及当开发的软件不符合适当标准时的后果。*编程语言和计算机体系结构的其他重要当前趋势也对这个问题产生了影响。动态编程语言如MatLab、R和Python作为科学家的应用编程语言正变得越来越流行，而Java脚本作为网络编程的一种方式正变得越来越流行。在架构方面，科学家拥有广泛的设备，包括工作站、笔记本电脑和移动设备，以及通过网络访问许多远程设备。此外，现在几乎所有设备都支持多核CPU和GPU的某种组合。*建议的研究的总体目标是开发新的编译器技术、软件开发工具和特定领域的语言，以帮助科学家有效地编程并充分利用计算机资源。我们建议的研究将建立在我们最近在McLab项目(www.sable.mcgill.ca/mclab)上所做的工作的基础上，该项目主要集中在编译器/VM工具和技术、语言扩展以及用于MATLAB的工具上。正如我们研究历史上的情况一样，我们将开发新的想法，将其作为开源项目实施，并在来自多个科学学科的各种基准测试上进行测试。*我们确定了五个相关的研究方向：(1)我们将支持将MatLab程序自动翻译到Java脚本，以便让科学家可以轻松地在Web上运行他们的代码；(2)我们将继续针对多核CPU和GPU的有效优化和代码生成工作；(3)我们将利用静态和动态程序分析为科学家开发编程工具；(4)我们将继续开展科学计算基准的工作，扩展到各种动态语言；(5)我们将致力于新的特定领域的编程语言，以减轻科学家的编程负担。*拟议的研究面向编译器研究人员(新技术和开源工具)和科学家最终用户。这项研究具有新颖性，因为它针对的是一个越来越重要的领域，即为科学家提供编程支持，并为现代CPU/GPU和基于Web的系统生成高效代码。**

Computation and programming are becoming increasingly important aspects of the work done by scientists. However, scientists face many challenges and do not necessarily have the proper languages, compilers, and software tools to efficiently and safely accomplish their goals. A 2010 article in Nature, entitled "Why scientific programming does not compute", describes the increasing importance of programming, the challenges faced by scientists, and the consequences when the software developed is not up to a proper standard.****Other important current trends in programming languages and computer architectures also impact on this problem. Dynamic programming languages such as MATLAB, R and Python are becoming increasingly popular as application programming languages for scientists, and JavaScript is becoming increasingly popular as a way of programming on the web. On the architecture side, scientists have at their disposal a wide range of devices including workstations, laptops, and mobile devices, as well as access to many remote devices via the web. Furthermore, almost all devices now support some combination of multicore CPU and GPUs. ******The overall objective the proposed research is to develop new compiler techniques, software development tools, and domain-specific languages which will help scientists program effectively and which will make the best use of computer resources.  Our proposed research will build upon our recent work on the McLab project (www.sable.mcgill.ca/mclab), which has concentrated on compiler/VM tools and techniques, language extensions, and tools for MATLAB. As has been the case historically in our research, we will develop new ideas, implement these as open source projects, and test them on a variety of benchmarks from a wide variety of scientific disciplines.***We have identified five related research directions:  (1) we will support automatic translation of MATLAB programs to JavaScript, so as to allow Scientists to easily run their code on the web; (2) we will continue our work on effective optimization and code generation for multicore CPUs and GPUs; (3) we will leverage static and dynamic program analysis to develop programming tools for scientists, (4) we will continue our work on benchmarks for scientific computations, expanding to a variety of dynamic languages; and (5)  we will work on new domain-specific programming languages in order to ease the programming burden on scientists.******The proposed research is intended to be used by both compiler researchers (new techniques and open source tools), and scientist end-users. The research is novel in that it is targeting an increasingly important area of enabling programming for scientists, and in generating efficient code for both modern CPU/GPUs and web-based systems.**