Firepile: Run-time compilation for GPUs in scala

GPCE'11 - Proceedings of the 10th International Conference on Generative Programming and Component Engineering

Volumn , Issue , 2011, Pages 107-115

  Nystrom, Nathaniel ^a   White, Derek ^b   Das, Kishen ^b  

^a UNIVERSITY OF LUGANO   (Switzerland)

^b UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

Author keywords

GPU; OpenCL; Run time code generation; Scala

Indexed keywords

C CODES; COMMODITY HARDWARE; DYNAMIC MEMORY ALLOCATION; FUNCTION VALUES; GPU; GPU PROGRAMMING; MEMORY HIERARCHY; META PROGRAMMING; OPENCL; OTHER APPLICATIONS; PARALLEL PROCESSOR; PROGRAMMING MODELS; RUN-TIME CODE GENERATION; RUNTIMES; SCALA;

AUTOMATIC PROGRAMMING; FORESTRY; MEMORY ARCHITECTURE; PARALLEL PROGRAMMING; PROGRAM PROCESSORS; STORAGE ALLOCATION (COMPUTER);

CODES (SYMBOLS);

COMPUTER PROGRAMING; COMPUTER PROGRAMS; DATA PROCESSING; FORESTRY; MATHEMATICAL MODELS;

EID: 81455154935     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2047862.2047883     Document Type: Conference Paper

References (34)

1. Aparapi: Java API for expressing GPU bound data parallel algorithms. http://developer.amd.com/zones/java/aparapi/Pages/default.aspx, 2011.
2. Joshua Auerbach, David F. Bacon, Perry Cheng, and Rodric Rabbah. Lime: A Java-compatible and synthesizable language for heterogeneous architectures. In Proceedings of the 25th ACM Conference on Object-Oriented Programming Systems, Languages and Applications (OOPSLA 2010), pages 89-108, 2010.
3. Alan Bawden. Quasiquotation in Lisp. In Partial Evaluation and Semantic-Based Program Manipulation, pages 4-12, 1999.
4. Ian Buck, Tim Foley, Daniel Horn, Jeremy Sugerman, Kayvon Fatahalian, Mike Houston, and Pat Hanrahan. Brook for GPUs: stream computing on graphics hardware. In ACM SIGGRAPH 2004 Papers (SIGGRAPH '04), pages 777-786, 2004.
5. Hassan Chafi, Zach DeVito, Adriaan Moors, Tiark Rompf, Arvind K. Sujeeth, Pat Hanrahan, Martin Odersky, and Kunle Olukotun. Language virtualization for heterogeneous parallel computing. In Onward! '10: Proceedings of the ACM International Conference on Object Oriented Programming Systems Languages and Applications, October 2010.
6. Olivier Chafik. JavaCL: Java wrappers for OpenCL. http://code.google.com/ p/javacl, 2011.
7. Olivier Chafik. ScalaCL: Faster Scala: optimizing compiler plugin + GPU-based collections (OpenCL). http://code.google.com/p/scalacl, 2011.
8. Clyther: Python language extension for OpenCL. http://clyther. sourceforge.net, 2011.
9. ECMA. Standard ECMA-334: C] language specification (4th edition). http://www.ecma-international.org/publications/standards/Ecma-334.htm, June 2006.
10. Miguel Garcia, Anastasia Izmaylova, and Sibylle Schupp. Extending Scala with database query capability. Journal of Object Technology, July 2010.
11. James Gosling, Bill Joy, Guy Steele, and Gilad Bracha. The Java Language Specification. Addison Wesley, 3rd edition, 2005. ISBN 0321246780.
12. GPU.NET: Library for developing GPU-accelerated applications with .NET. http://www.tidepowerd.com/product, 2011.
13. Shan Shan Huang, Amir Hormati, David F. Bacon, and Rodric Rabbah. Liquid metal: Object-oriented programming across the hardware/software boundary. In Proceedings of the 22nd European Conference on Object-Oriented Programming (ECOOP 2008), volume 5142 of Lecture Notes in Computer Science, pages 76-103, 2008.
14. JOCL: Java bindings for OpenCL. http://www.jocl.org 2011.
15. 5 report on the algorithmic language Scheme. ACM SIGPLAN Notices, 33(9):26-76, October 1998.
16. Andreas Klöckner, Nicolas Pinto, Yunsup Lee, Bryan C. Catanzaro, Paul Ivanov, and Ahmed Fasih. PyCUDA: GPU run-time code generation for high-performance computing. http://arxiv.org/abs/0911.3456, 2009. In submission.
17. G. Korland, N. Shavit, and P. Felber. Noninvasive concurrency with Java STM. In Third Workshop on Programmability Issues for Multi- Core Computers (MULTIPROG-3), January 2010.
18. Sean Lee, Vinod Grover, Manuel M. T. Chakravarty, and Gabriele Keller. GPU kernels as data-parallel array computations in Haskell. In Workshop on Exploiting Parallelism using GPUs and other Hardware- Assisted Methods (EPHAM), 2009.
19. Calle Lejdfors and Lennart Ohlsson. Implementing an embedded gpu language by combining translation and generation. In Proceedings of the 2006 ACM symposium on Applied computing (SAC '06), pages 1610-1614, 2006. (Pubitemid 44759056)
20. Geoffrey Mainland and Greg Morrisett. Nikola: embedding compiled GPU functions in Haskell. In Proceedings of the third ACM symposium on Haskell (Haskell '10), pages 67-78, 2010.
21. Geoffrey B. Mainland. Why it's nice to be quoted: Quasiquoting for Haskell. In Proceedings of the 2007 ACM symposium on Haskell (Haskell '07), 2007.
22. A. Munshi and Khronos OpenCL Working Group. The OpenCL specification, 2009.
23. NVIDIA. Compute unified device architecture programming guide. http://developer.download.nvidia.com/compute/cuda/10/ NVIDIACUDAProgrammingGuide1.0.pdf, 2008.
24. NVIDIA. NVIDIA OpenCL best practices guide, version 1.0. http://www.nvidia.com/content/cudazone/CUDABrowser/downloads/papers/ NVIDIAOpenCLBestPracticesGuide.pdf, 2009.
25. NVIDIA. NVIDIA's next generation CUDA compute architecture: Fermi. http://www.nvidia.com/content/PDF/fermiwhitepapers/ NVIDIAFermiComputeArchitectureWhitepaper.pdf, 2010.
26. Martin Odersky et al. The Scala language specification, 2006-2011.
27. PyOpenCL: Python programming environment for OpenCL. http://mathema. tician.de/software/pyopencl, 2011.
28. Johannes Rudolph and Peter Thiemann. Mnemonics: type-safe bytecode generation at run time. In Proceedings of the 2010 ACM SIGPLAN workshop on Partial evaluation and program manipulation (PEPM), pages 15-24, 2010.
29. Guy L. Steele, Jr. and Richard P. Gabriel. The evolution of Lisp. In HOPL-II: The second ACM SIGPLAN conference on History of programming languages, pages 231-270, New York, NY, USA, 1993. ACM.
30. Walid Taha. A gentle introduction to multi-stage programming. In Domain-Specific Program Generation, pages 30-50, 2003. (Pubitemid 38803765)
31. Walid Taha and Tim Sheard. Multi-stage programming with explicit annotations. In Proceedings of the ACM-SIGPLAN Symposium on Partial Evaluation and semantic based program manipulations (PEPM), pages 203-217, 1997.
32. David Tarditi, Sidd Puri, and Jose Oglesby. Accelerator: Using data parallelism to program GPUs for general-purpose uses. In Proceedings of the 15th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), October 2006.
33. Raja Vallée-Rai, Phong Co, Etienne Gagnon, Laurie Hendren, Patrick Lam, and Vijay Vijay Sundaresan. Soot: A Java bytecode optimization framework. In Proceedings of the 1999 conference of the Centre for Advanced Studies on Collaborative research (CASCON), 1999.
34. Yonghong Yan, Max Grossman, and Vivek Sarkar. JCUDA: A programmer-friendly interface for accelerating Java programs with CUDA. In Proceedings of the 15th International Euro-Par Conference on Parallel Processing (Euro-Par '09), pages 887-899, 2009.