Terra: a multi-stage language for high-performance computing

  • Authors:

  • Zachary DeVito;James Hegarty;Alex Aiken;Pat Hanrahan;Jan Vitek

  • Affiliations:

  • Stanford University, Stanford, USA;Stanford University, Stanford, USA;Stanford University, Stanford, USA;Stanford University, Stanford, USA;Purdue University, West Lafayette, USA

  • Venue:
  • Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation
  • Year:
  • 2013

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Abstract

High-performance computing applications, such as auto-tuners and domain-specific languages, rely on generative programming techniques to achieve high performance and portability. However, these systems are often implemented in multiple disparate languages and perform code generation in a separate process from program execution, making certain optimizations difficult to engineer. We leverage a popular scripting language, Lua, to stage the execution of a novel low-level language, Terra. Users can implement optimizations in the high-level language, and use built-in constructs to generate and execute high-performance Terra code. To simplify meta-programming, Lua and Terra share the same lexical environment, but, to ensure performance, Terra code can execute independently of Lua's runtime. We evaluate our design by reimplementing existing multi-language systems entirely in Terra. Our Terra-based auto-tuner for BLAS routines performs within 20% of ATLAS, and our DSL for stencil computations runs 2.3x faster than hand-written C.