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，科学家们面临着许多挑战，不一定有合适的语言，编译器和软件工具来有效和安全地实现他们的目标。 2010年《自然》杂志上一篇题为《为什么科学编程不能计算》的文章描述了编程的重要性日益增加，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趋势也影响了这个问题。 MATLAB、R和Python等动态编程语言作为科学家的应用程序编程语言越来越受欢迎，而JavaScript作为Web上的编程方式也越来越受欢迎。 在架构方面，科学家可以使用各种设备，包括工作站、笔记本电脑和移动的设备，以及通过网络访问许多远程设备。 此外，几乎所有的设备现在都支持多核CPU和GPU的某种组合。 * * 拟议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，这将有助于科学家有效地编程，并充分利用计算机资源。 我们提出的研究将建立在我们最近的McLab项目（www.sable.mcgill.ca/mclab）的工作，该项目集中在编译器/VM工具和技术，语言扩展和MATLAB工具上。 正如我们研究的历史一样，我们将开发新的想法，将其作为开源项目实施，并在各种科学学科的各种基准上对其进行测试。我们已经确定了五个相关的研究方向：（1）我们将支持MATLAB程序到JavaScript的自动翻译，以便科学家可以轻松地在Web上运行他们的代码;（2）我们将继续我们的工作，为多核CPU和GPU进行有效的优化和代码生成;（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）我们将继续研究科学计算的基准，扩展到各种动态语言;（5）我们将致力于开发新的特定领域编程语言，以减轻科学家的编程负担。拟议的研究旨在由编译器研究人员（新技术和开源工具）和科学家最终用户使用。 这项研究的新颖之处在于，它针对的是一个越来越重要的领域，即为科学家提供编程能力，以及为现代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.**