SHF: AF: Medium: Collaborative Research:The Ponchoir Stencil Complier

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

Many high-end scientific applications perform stencil computations in their inner loops. A stencil defines the value of a grid point in a d-dimensional spatial grid at time t as a function of neighboring grid points at recent times before t. Stencil computations are conceptually simple to implement using nested loops, but looping implementations suffer from poor cache performance on multicore processors. Cache-oblivious divide-and-conquer stencil codes can achieve an order of magnitude improvement in cache efficiency over looping implementations, but most programmers find it difficult to write cache-oblivious stencil codes. Moreover, open problems remain in adapting these algorithms to realistic applications that lack the perfect regularity of simple examples. This project's investigation of cache-oblivious stencil compilation enables ordinary programmers of stencil computations to enjoy the benefits of multicore technology without requiring them to write code any more complex than naive nested loops. The research project is developing a language embedded in C++ that can express stencil computations concisely and can be compiled automatically into highly efficient algorithmic code for multicore processors and other platforms. The Pochoir stencil compiler compiles stencil computations that exhibit complex boundary conditions, such as periodic, constant, Dirichlet, Neumann, mirrored, and phase factors; irregularities, including macroscopic and microscopic inhomogeneities, as well as irregular shapes; general complex dependencies, such as push dependencies, horizontal dependencies, and dynamic dependencies. To achieve these goals, the researchers are developing provably good algorithms for complex stencil computations; exploring how domain-specific compiler technology can achieve speedups from efficient cache management, processor-pipeline scheduling, and parallel computation; investigating how to run stencils efficiently on a wide variety of architectures such as multicore, distributed-memory clusters, graphical processing units, FPGA's, and future exascale machines; demonstrating the effectiveness of their research by developing a production-quality stencil compiler; developing a benchmark suite and benchmarking system for evaluating Pochoir. This research enables scientific researchers and others to easily produce highly efficient codes for complex stencil computations. The codes make good use of the memory hierarchy and processor pipelines endemic to multicore processors and run fast on a diverse set of hardware platforms. This research eases the development and maintenance of a wide variety of stencil-based applications, ranging across physics, biology, chemistry, energy, climate, mechanical and electrical engineering, finance, and other areas, benefiting these application areas, as well as society at large.