Simple Universal Translator as an Alternative Compiler-Compiler

Simple item page
dc.citation.epage109
dc.citation.issue2
dc.citation.journalTitleAdvances in Cyber-Physical Systems
dc.citation.spage105
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorMelnyk, Anatoliy
dc.contributor.authorKozak, Nazar
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2020-06-16T08:12:18Z
dc.date.available2020-06-16T08:12:18Z
dc.date.created2019-02-26
dc.date.issued2019-02-26
dc.description.abstractThis article deals with ways of how to implement a simple universal translator. Such universal translator may be an alternative to the compiler-compiler.
dc.format.extent105-109
dc.format.pages5
dc.identifier.citationMelnyk A. Simple Universal Translator as an Alternative Compiler-Compiler / Anatoliy Melnyk, Nazar Kozak // Advances in Cyber-Physical Systems. — Lviv : Lviv Politechnic Publishing House, 2019. — Vol 4. — No 2. — P. 105–109.
dc.identifier.citationenMelnyk A. Simple Universal Translator as an Alternative Compiler-Compiler / Anatoliy Melnyk, Nazar Kozak // Advances in Cyber-Physical Systems. — Lviv : Lviv Politechnic Publishing House, 2019. — Vol 4. — No 2. — P. 105–109.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/52233
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofAdvances in Cyber-Physical Systems, 2 (4), 2019
dc.relation.ispartofAdvances in Cyber-Physical Systems, 2 (4), 2019
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dc.relation.references[2] Peter Mosses. SIS: A Compiler-Generator System Using Denotational Semantics, Report 78-4-3, Dept. of Computer Science, University of Aarhus, Denmark, June 1978.
dc.relation.references[3] C. Stephen Carr, David A. Luther, Sherian Erdmann, The TREEMETA Compiler-Compiler System: A Meta Compiler System for the Univac 1108 and General Electric 645, University of Utah Technical Report RADC-TR-69-83.
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dc.relation.references[6] Levine, John R.; Mason, Tony; Brown, Doug (1992). lex & yacc (2 ed.). O'Reilly. pp. 1–2. ISBN 1-56592-000-7.
dc.relation.references[7] The LLVM Compiler Infrastructure Project. Retrieved March 11, 2016.
dc.relation.references[8] Melnyk, A., Salo, A., Klymenko, V., Tsyhylyk, L. Chameleon – system for specialized processors high-level synthesis, Scientifictechnical magazine of National Aerospace University “KhAI”, Kharkiv, 2009. Nо. 5, P. 189–195.
dc.relation.references[9] S.-I. Lee, T. Johnson, and R. Eigenmann. Cetus – an extensible compiler infrastructure for source-to-source transformation. In Proc. Workshops on Languages and Compilers for Parallel Computing, 2003.
dc.relation.references[10] S. Lee, S.-J. Min, and R. Eigenmann. OpenMP to GPGPU: A compiler framework for automatic translation and optimization. In Proc. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009.
dc.relation.references[11] Y. Liu, E. Z. Zhang, amd X. Shen. A Cross-Input Adaptive Framework for GPU Program Optimization. In Proc. IEEE International Parallel & Distributed Processing Symposium, 2009.
dc.relation.references[12] M. Baskaran, U. Bondhugula, S. Krishnamoorthy, J. Ramanujam, A. Rountev, and P. Sadayappan. Automatic Data Movement and Computation Mapping for Multi-level Parallel Architectures with Explicitly Managed Memories. In Proc. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2008.
dc.relation.references[13] L.-N. Pouchet, C. Bastoul, A. Cohen, and N. Vasilache. Iterative optimization in the polyhedral mode: part I, on dimensional time. In Proc. International Symposium on Code Generation and Optimization, 2007.
dc.relation.references[14] K. Datta, M. Murphy, V. Volkov, S. Williams, J. Carter, L. Oliker, D. Patterson, J. Shalf, and K. Yelick. Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures, in Proceedings of the 2008 ACM/IEEE conference on Supercomputing, 2008, p. 4.
dc.relation.references[15] J. Ansel, Y. L. W. ans Cy Chan, M. Olszewski, A. Edelman, and S. Amarasinghe. Language and compiler support for auto-tuning variable-accuracy algorithms, in The International Symposium on Code Generation and Optimization, ser. CGO ’11, 2011.
dc.relation.references[16] J. Kurzak, H. Anzt, M. Gates, and J. Dongarra. Implementation and tuning of batched Cholesky factorization and solve for NVIDIA GPUs, IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 7, 2016.
dc.relation.references[17] A. Magni, C. Dubach, and M. O’Boyle. Automatic optimization of thread-coarsening for graphics processors, in Proceedings of the 23rd International Conference on Parallel Architectures and Compilation, ser. PACT ’14, 2014, pp. 455–466.
dc.relation.references[18] S. Unkule, C. Shaltz, and A. Qasem. Automatic restructuring of GPU kernels for exploiting inter-thread data locality, in Proceedings of the 21st International Conference on Compiler Construction, ser. CC’12, 2012, pp. 21–40.
dc.relation.references[19] Y. Yang, P. Xiang, J. Kong, M. Mantor, and H. Zhou. A unified optimizing compiler framework for different gpgpu architectures, ACM Trans. Archit. Code Optim., vol. 9, no. 2, pp. 9:1–9:33, 2012.
dc.relation.references[20] C. Lattner and V. Adve. LLVM: A compilation framework for lifelong program analysis & transformation, in Proceedings of the International Symposium on Code Generation and Optimization: Feedback directed and Runtime Optimization, ser. CGO ’04, 2004.
dc.relation.references[21] F. Bodin, T. Kisuki, P. Knijnenburg, M. O’Boyle, and E. Rohou. Iterative compilation in a non-linear optimisation space, in Workshop on Profile and Feedback-Directed Compilation, 1998.
dc.relation.references[22] P. M. Knijnenburg, T. Kisuki, and M. F. O’Boyle. Combined selection of tile sizes and unroll factors using iterative compilation, The Journal of Supercomputing, vol. 24, no. 1, pp. 43–67, 2003.
dc.relation.references[23] F. Agakov, E. Bonilla, J. Cavazos, B. Franke, G. Fursin, M. F. P. O’Boyle, J. Thomson, M. Toussaint, and C. K. I. Williams. Using machine learning to focus the iterative optimization, in Proceedings of the International Symposium on Code Generation and Optimization, ser. CGO ’06, 2006, pp. 295–305.
dc.relation.referencesen[1] Aho, Sethi, Ullman, Compilers: Principles, Techniques, and Tools, Addison-Wesley, 1986. ISBN 0-201-10088-6.
dc.relation.referencesen[2] Peter Mosses. SIS: A Compiler-Generator System Using Denotational Semantics, Report 78-4-3, Dept. of Computer Science, University of Aarhus, Denmark, June 1978.
dc.relation.referencesen[3] C. Stephen Carr, David A. Luther, Sherian Erdmann, The TREEMETA Compiler-Compiler System: A Meta Compiler System for the Univac 1108 and General Electric 645, University of Utah Technical Report RADC-TR-69-83.
dc.relation.referencesen[4] Spirit 2.5.5. https://www.boost.org/doc/libs/1_67_0/libs/spirit/doc/html/index.html 12.12.2019.
dc.relation.referencesen[5] Lesk, M.E.; Schmidt, E. "Lex – A Lexical Analyzer Generator". Retrieved August 16, 2010.
dc.relation.referencesen[6] Levine, John R.; Mason, Tony; Brown, Doug (1992). lex & yacc (2 ed.). O'Reilly. pp. 1–2. ISBN 1-56592-000-7.
dc.relation.referencesen[7] The LLVM Compiler Infrastructure Project. Retrieved March 11, 2016.
dc.relation.referencesen[8] Melnyk, A., Salo, A., Klymenko, V., Tsyhylyk, L. Chameleon – system for specialized processors high-level synthesis, Scientifictechnical magazine of National Aerospace University "KhAI", Kharkiv, 2009. No. 5, P. 189–195.
dc.relation.referencesen[9] S.-I. Lee, T. Johnson, and R. Eigenmann. Cetus – an extensible compiler infrastructure for source-to-source transformation. In Proc. Workshops on Languages and Compilers for Parallel Computing, 2003.
dc.relation.referencesen[10] S. Lee, S.-J. Min, and R. Eigenmann. OpenMP to GPGPU: A compiler framework for automatic translation and optimization. In Proc. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009.
dc.relation.referencesen[11] Y. Liu, E. Z. Zhang, amd X. Shen. A Cross-Input Adaptive Framework for GPU Program Optimization. In Proc. IEEE International Parallel & Distributed Processing Symposium, 2009.
dc.relation.referencesen[12] M. Baskaran, U. Bondhugula, S. Krishnamoorthy, J. Ramanujam, A. Rountev, and P. Sadayappan. Automatic Data Movement and Computation Mapping for Multi-level Parallel Architectures with Explicitly Managed Memories. In Proc. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2008.
dc.relation.referencesen[13] L.-N. Pouchet, C. Bastoul, A. Cohen, and N. Vasilache. Iterative optimization in the polyhedral mode: part I, on dimensional time. In Proc. International Symposium on Code Generation and Optimization, 2007.
dc.relation.referencesen[14] K. Datta, M. Murphy, V. Volkov, S. Williams, J. Carter, L. Oliker, D. Patterson, J. Shalf, and K. Yelick. Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures, in Proceedings of the 2008 ACM/IEEE conference on Supercomputing, 2008, p. 4.
dc.relation.referencesen[15] J. Ansel, Y. L. W. ans Cy Chan, M. Olszewski, A. Edelman, and S. Amarasinghe. Language and compiler support for auto-tuning variable-accuracy algorithms, in The International Symposium on Code Generation and Optimization, ser. CGO ’11, 2011.
dc.relation.referencesen[16] J. Kurzak, H. Anzt, M. Gates, and J. Dongarra. Implementation and tuning of batched Cholesky factorization and solve for NVIDIA GPUs, IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 7, 2016.
dc.relation.referencesen[17] A. Magni, C. Dubach, and M. O’Boyle. Automatic optimization of thread-coarsening for graphics processors, in Proceedings of the 23rd International Conference on Parallel Architectures and Compilation, ser. PACT ’14, 2014, pp. 455–466.
dc.relation.referencesen[18] S. Unkule, C. Shaltz, and A. Qasem. Automatic restructuring of GPU kernels for exploiting inter-thread data locality, in Proceedings of the 21st International Conference on Compiler Construction, ser. CC’12, 2012, pp. 21–40.
dc.relation.referencesen[19] Y. Yang, P. Xiang, J. Kong, M. Mantor, and H. Zhou. A unified optimizing compiler framework for different gpgpu architectures, ACM Trans. Archit. Code Optim., vol. 9, no. 2, pp. 9:1–9:33, 2012.
dc.relation.referencesen[20] C. Lattner and V. Adve. LLVM: A compilation framework for lifelong program analysis & transformation, in Proceedings of the International Symposium on Code Generation and Optimization: Feedback directed and Runtime Optimization, ser. CGO ’04, 2004.
dc.relation.referencesen[21] F. Bodin, T. Kisuki, P. Knijnenburg, M. O’Boyle, and E. Rohou. Iterative compilation in a non-linear optimisation space, in Workshop on Profile and Feedback-Directed Compilation, 1998.
dc.relation.referencesen[22] P. M. Knijnenburg, T. Kisuki, and M. F. O’Boyle. Combined selection of tile sizes and unroll factors using iterative compilation, The Journal of Supercomputing, vol. 24, no. 1, pp. 43–67, 2003.
dc.relation.referencesen[23] F. Agakov, E. Bonilla, J. Cavazos, B. Franke, G. Fursin, M. F. P. O’Boyle, J. Thomson, M. Toussaint, and C. K. I. Williams. Using machine learning to focus the iterative optimization, in Proceedings of the International Symposium on Code Generation and Optimization, ser. CGO ’06, 2006, pp. 295–305.
dc.relation.urihttps://www.boost.org/doc/libs/1_67_0/libs/spirit/doc/html/index.html
dc.rights.holder© Національний університет “Львівська політехніка”, 2019
dc.rights.holder© Melnyk A., Kozak N., 2019
dc.subjectcompiler-compiler
dc.subjectuniversal translator
dc.subjectBackus–Naur form
dc.titleSimple Universal Translator as an Alternative Compiler-Compiler
dc.typeArticle

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Advances In Cyber-Physical Systems. – 2019. – Vol. 4, No. 2