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| Content Provider | ACM Digital Library |
|---|---|
| Author | DeVito, Zachary Hanrahan, Pat Hegarty, James Aiken, Alex Vitek, Jan |
| 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. |
| Starting Page | 105 |
| Ending Page | 116 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450320146 |
| DOI | 10.1145/2491956.2462166 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-06-16 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Staged computation Lua Dsl |
| Content Type | Text |
| Resource Type | Article |
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