Abstract.
This paper proposes a new software architecture framework, named FIBER, to generalize auto-tuning facilities and obtain highly accurate estimated parameters. The FIBER framework also provides a loop unrolling function, needing code generation and parameter registration processes, to support code development by library developers. FIBER has three kinds of parameter optimization layers–installation, before execution-invocation, and run-time. An eigensolver parameter to apply the FIBER framework is described and evaluated in three kinds of parallel computers; the HITACHI SR8000/MPP, Fujitsu VPP800/63, and Pentium4 PC cluster. Evaluation indicated a 28.7% speed increase in the computation kernel of the eigensolver with application of the new optimization layer of before execution-invocation.
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References
ATLAS Project, available at http://www.netlib.org/atlas/index.html
Bilmes, J., Asanović, K., Chin, C.-W., Demmel, J.: Optimizing matrix multiply using PHiPAC: a portable, high-performance, ANSI C coding methodology. In: Proceedings of International Conference on Supercomputing 1997, pp. 340–347 (1997)
Frigo, M.: A fast Fourier transform compiler. In: Proceedings of the 1999 ACM SIGPLAN Conference on Programming Language Design and Implementation, Atlanta, Georgia, May 1999, pp. 169–180 (1999)
Katagiri, T., Kuroda, H., Ohsawa, K., Kudoh, M., Kanada, Y.: Impact of autotuning facilities for parallel numerical library. IPSJ Transaction on High Performance Computing Systems 42(SIG 12 (HPS 4)), 60–76 (2001)
Kuroda, H., Katagiri, T., Kanada, Y.: Knowledge discovery in auto-tuning parallel numerical library. In: Arikawa, S., Shinohara, A. (eds.) Progress in Discovery Science. LNCS (LNAI), vol. 2281, pp. 628–639. Springer, Heidelberg (2002)
Naono, K., Yamamoto, Y.: A framework for development of the library for massively parallel processors with auto-tuning function and the single memory interface. IPSJ SIG Notes (2001-HPC-87), 25–30 (2001)
Ribler, R.L., Simitci, H., Reed, D.A.: The AutoPilot performance-directed adaptive control system. Future Generation Computer Systems, special issue (Performance Data Mining) 18(1), 175–187 (2001)
Takahiro, K., Kise, K., Honda, H., Yuba, T.: FIBER: A framework of installation, before execution-invocation, and run-time optimization layers for auto-tuning software. IS Technical Report, Graduate School of Information Systems, The University of Electro-Communications, UEC-IS-2003-3 (May 2003)
Tapus, C., Chung, I.-H., Hollingsworth, J.K.: Active Harmony: Towards automated performance tuning. In: Proceedings of High Performance Networking and Computing (SC 2002), Baltimore, USA (November 2003)
Whaley, R., Petitet, A., Dongarra, J.J.: Automated empirical optimizations of software and the ATLAS project. Parallel Computing 27, 3–35 (2001)
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Katagiri, T., Kise, K., Honda, H., Yuba, T. (2003). FIBER: A Generalized Framework for Auto-tuning Software. In: Veidenbaum, A., Joe, K., Amano, H., Aiso, H. (eds) High Performance Computing. ISHPC 2003. Lecture Notes in Computer Science, vol 2858. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39707-6_11
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DOI: https://doi.org/10.1007/978-3-540-39707-6_11
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