XPS: EXPL: DSD: Portal: A Language and Compiler for Parallel N-body Computations

职务名称：XPS：EXPL：渠务署：入口：一种用于并行N体计算的语言和编译器现代机器变得越来越复杂，导致即使是最先进的编译器也无法生成最优化的代码。因此，在纸上设计的算法和在十亿核系统上有效运行的代码之间存在很大的差距。本研究计画的目的是透过发展Portal，一种新的高效能领域特定语言（DSL）和编译器，来弥补这一差距。这些问题在各个领域都有应用，从分子动力学、天体物理学、声学、流体动力学的科学计算模拟到大数据问题。在Portal中，领域科学家可以编写高级别的程序，同时获得由专家在现代大规模并行机器上编写的高度调优和优化的低级代码的性能。智力的优点是显示一个DSL与高层次的制定可以直接导致两个渐近快速算法和高效的并行实现各种不同的架构。该项目更广泛的意义和重要性是免费提供的软件，使领域科学家能够利用并行计算的性能，并使科学发现不仅在科学计算和机器学习中，而且在统计学，计算机图形学，计算几何学和应用数学等领域的许多相关问题中。Portal的目标有三个方面：（a）实现可扩展的、快速的、渐近最优的基于树的N体算法;（B）设计一种直观的语言和API，以实现各种算法的快速实现;（c）使大规模并行问题能够在当前和未来的exascale机器上运行。更重要的是，语言和中间算法表示独立于架构，使这种方法可移植，易于扩展到从ARM/x86 CPU到GPU的不同平台。该项目旨在解决重要的软件问题，这些问题将允许大规模数据集上的N体问题的互操作性和可扩展性。

Title: XPS: EXPL: DSD: Portal: A Language and Compiler for Parallel N-body ComputationsModern machines are becoming increasingly more complex resulting in even the most advanced compilers failing to generate the best optimized code. As a result, there is a big gap between the algorithm one designs on paper and the code that runs efficiently on a billion-core system. This research project aims to bridge this gap by developing Portal, a new high-performance domain-specific language(DSL) and compiler, for the domain of N-body problems. Such problems have applications in various areas ranging from scientific computing simulations in molecular dynamics, astrophysics, acoustics, fluid dynamics all the way to big data problems. In Portal, domain scientists can write programs at a high level while obtaining the performance of highly tuned and optimized low level code written by experts on modern massively parallel machines. The intellectual merit is to show how a DSL with a high-level formulation can lead directly to both asymptotically fast algorithms and their efficient parallel implementations on a variety of distinct architectures. The project's broader significance and importance are freely available software to enable domain scientists to harness the performance power of parallel computing and enabling scientific discovery not only in scientific computing and machine learning but also in a number of related problems in domains such as statistics, computer graphics, computational geometry, and applied mathematics. These problems can be expressed in Portal to obtain an out-of-the-box parallel optimized implementation.The goals of Portal are three-fold: (a) to implement scalable, fast, and asymptotically optimal tree-based N-body algorithms, (b) to design an intuitive language and API to enable rapid implementations of a variety of algorithms, and (c) to enable parallel large-scale problems to run on current and future exascale machines. More importantly, the language and intermediate algorithm representation are independent of the architecture, making this approach portable and easily extensible to different platforms from ARM/x86 CPUs to GPUs. The project aims to solve important software issues that will allow for interoperability and scalability of N-body problems on massive datasets.