Abstract
Several representative scientific computing applications have been mapped on the stream processor. But most of them are computation-intensive kernels or synthetic benchmarks. In this paper, we implement and optimize a complete data-intensive hydrodynamics application, QNJ-5, on the stream processor which is designed for computation-intensive applications. Different from other stream programs, how to relieve memory access pressure is especially important to this stream program. Simulation results show that StreamQNJ-5 gets an ultimate speedup of 2.97 and 1.11 over original FORTRAN QNJ-5 on a Xeon and Iantium processor, respectively.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dally, W.J., Hanrahan, P., Erez, M., Knight, T.J., Labonté, F., Ahn, J.-H., Jayasena, N., Kapasi, U.J., Das, A., Gummaraju, J., Buck, I.: Merrimac: Supercomputing with Streams, SC, November 2003, Phoenix, Arizona (2003)
Erez, M., Ahn, J.H., Jayasena, N., Knight, T.J., Das, A., Labonté, F., Gummaraju, J., Dally, W.J., Hanrahan, P., Rosenblum, M.: Merrimac - Supercomputing with Streams. In: Proceedings of the 2004 SIGGRAPH GP2 Workshop on General Purpose Computing on Graphics Processors, June 2004, Los Angeles, California (2004)
Merrimac – Stanford Streaming Supercomputer Project, Stanford University, http://merrimac.stanford.edu/
Fatica, M., Jameson, A., Alonso, J.J.: StreamFLO: an Euler Solver for Streaming Architectures, IAA Paper 2004-1090. In: 42nd Aerospace Sciences Meeting and Exhibit Conference, Reno (January 2004)
Narayanan, M., Oliker, L., Janin, A., Husbands, P., Li, X.S.: Scientific kernels on VIRAM and imagine media processors. Lawrence Berkeley National Laboratory. Paper LBNL-54908 (October 10, 2002)
Erez, M., Ahn, J.H., Garg, A., Dally, W.J., Darve, E.: Analysis and Performance Results of a Molecular Modeling Application on Merrimac, SC’04, Pittsburgh, Pennsylvania, USA (November 2004)
Guibin, W., Yuhua, T., et al.: Application and Study of Scientific Computing on Stream Processor. Advances on Computer Architecture (ACA’06), August, Chengdu, China (2006)
Jing, D., Xuejun, Y., et al.: Implementation and Evaluation of Scientific Computing Programs on Imagine. Advances on Computer Architecture (ACA’06), Chengdu, China (August 2006)
Khailany, B.: The VLSI Implementation and Evaluation of Area- and Energy-Efficient Streaming Media Processors, Ph.D. Thesis, Dept. of Electrical Engineering, Stanford University (2003)
Saman Amarasinghe, W.: Stream Architectures. In: Malyshkin, V. (ed.) PaCT 2003. LNCS, vol. 2763, Springer, Heidelberg (2003)
Rixner, M.: Stream Processor Architecture. Kluwer Academic Publishers, Boston, MA (2001)
Kapasi, U.J., Rixner, S., et al.: Programmable Stream Processor. IEEE Computer, Los Alamitos (2003)
Mattson, P.: A Programming System for the Imagine Media Processor. Dept.of Electrical Engineering. Ph.D. thesis, Stanford University (2002)
Mattson, P., et al.: Imagine Programming System Developer’s Guide (2004)
Das, A., Mattson, P., et al.: Imagine Programming System User’s Guide 2.0 (June 2004)
The Imagine Project, Stanford University, http://cva.stanford.edu/imagine/
Kapasi, U.J., Dally, W.J., et al.: The Imagine Stream Processor. In: Processings of the 2002 International Conference on Computer Design (2002)
Chan, T.F., Gallopoulos, E., Simoncini, V., Szeto, T., Tong, C.H.: A Quasi-Minimal Residual Variant Of The Bi-Cgstab Algorithm For Nonsymmetric Systems. SIAM Journal on Scientific Computing (1994)
Rixner, S., Dally, W.J., Kapasi, U.J., Mattson, P., Owens, J.D.: Memory Access Scheduling. In: 27th Annual International Symposium on Computer Architecture, Vancouver, Canada, pp. 128–138 (June 2000)
Lawson, C.L., Hanson, R.J., Kincaid, D., Krogh, F.T.: Basic Linear Algebra Subprograms for FORTRAN Usage. ACM Trans. Math. Soft. 5, 308–323 (1979)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, Y., Li, G., Yang, X. (2007). Implementing and Optimizing a Data-Intensive Hydrodynamics Application on the Stream Processor. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74484-9_31
Download citation
DOI: https://doi.org/10.1007/978-3-540-74484-9_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74482-5
Online ISBN: 978-3-540-74484-9
eBook Packages: Computer ScienceComputer Science (R0)