The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
POLLY — PERFORMING POLYHEDRAL OPTIMIZATIONS ON A LOW-LEVEL INTERMEDIATE REPRESENTATION
Abstract
The polyhedral model for loop parallelization has proved to be an effective tool for advanced optimization and automatic parallelization of programs in higher-level languages. Yet, to integrate such optimizations seamlessly into production compilers, they must be performed on the compiler's internal, low-level, intermediate representation (IR). With Polly, we present an infrastructure for polyhedral optimizations on such an IR. We describe the detection of program parts amenable to a polyhedral optimization (so-called static control parts), their translation to a Z-polyhedral representation, optimizations on this representation and the generation of optimized IR code. Furthermore, we define an interface for connecting external optimizers and present a novel way of using the parallelism they introduce to generate SIMD and OpenMP code. To evaluate Polly, we compile the PolyBench 2.0 benchmarks fully automatically with PLuTo as external optimizer and parallelizer. We can report on significant speedups.
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Cites
The application/json Media Type for JavaScript Object Notation (JSON)
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A practical automatic polyhedral parallelizer and locality optimizer
Bondhugula, U., Hartono, A., Ramanujam, J., & Sadayappan, P. (2008) · Proceedings of the 29th ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/1375581.1375595 · Cited by 880
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Native Client: A Sandbox for Portable, Untrusted x86 Native Code
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LegUp: high-level synthesis for FPGA-based processor/accelerator systems
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Code generation in the polyhedral model is easier than you think
Bastoul, C. (2004) · Proceedings. 13th International Conference on Parallel Architecture and Compilation Techniques, 2004. PACT 2004. · doi:10.1109/pact.2004.1342537 · Cited by 447
isl: An Integer Set Library for the Polyhedral Model
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The Polyhedral Model Is More Widely Applicable Than You Think
Benabderrahmane, M.-W., Pouchet, L.-N., Cohen, A., & Bastoul, C. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-11970-5_16 · Cited by 232
Semi-Automatic Composition of Loop Transformations for Deep Parallelism and Memory Hierarchies
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Automatic C-to-CUDA Code Generation for Affine Programs
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Cited by
Data Movement Is All You Need: A Case Study on Optimizing Transformers
Ivanov, A., Dryden, N., Ben-Nun, T., Li, S., & Hoefler, T. (2020) · arXiv · doi:10.48550/arxiv.2007.00072 · Cited by 78
Metadata
- Authors
- GROSSER, T., GROESSLINGER, A., & LENGAUER, C.
- Venue
- Parallel Processing Letters
- Publisher
- World Scientific Pub Co Pte Lt
- Published
- 2012-12
- Volume
- 22
- Issue
- 04
- Pages
- 1250010
- ISSN
- 0129-6264 (ISSN-L)
- 1793-642X
- OpenAlex
- W2102976251
- Cited by
- 355
- References
- 15
- FWCI
- 16.95
- Type
- journal article
- Language
- en
- Open access
- closed
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