出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3524059.3532389
关键词
parallelism; dataflow analysis; automatic parallelization
类别
资金
- EuroHPC-JU [101034126]
- European Union's Horizon2020 programme
- European Research Council under the PSAP grant [101002047]
- RED-SEA project [955776]
- DEEP-SEA project [955606]
The research proposes lifting C programs to a parametric dataflow representation for static data-centric analysis and automatic high-performance code generation. By separating writing code from optimizing for different hardware, efficient specialized versions can be generated from simple, portable C source code with the click of a button. This approach can identify parallelism and outperform existing compilers.
C is the lingua franca of programming and almost any device can be programmed using C. However, programming modern heterogeneous architectures such as multi-core CPUs and GPUs requires explicitly expressing parallelism as well as device-specific properties such as memory hierarchies. The resulting code is often hard to understand, debug, and modify for different architectures. We propose to lift C programs to a parametric dataflow representation that lends itself to static data-centric analysis and enables automatic high-performance code generation. We separate writing code from optimizing for different hardware: simple, portable C source code is used to generate efficient specialized versions with a click of a button. Our approach can identify parallelism when no other compiler can, and outperforms a bespoke parallelized version of a scientific proxy application by up to 21%.
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