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Cache Efficiency and Scalability on Multi-core Architectures

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Parallel Computing Technologies (PaCT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6873))

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Abstract

Two electrical engineering applications from industry partners dealing with sparse matrices were analyzed regarding cache efficiency and scalability on modern multi core systems. Two different contemporary multi-core architectures have been investigated, namely Intel’s Westmere and AMD’s Magny-Cours. This paper can be regarded as a continuation of the investigations presented in [14] and [15].

In addition, the SuiteSparseQR library for efficiently computing QR factorizations of sparse matrices was evaluated regarding scalability and cache efficiency.

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References

  1. OpenMP: The OpenMP API specification for parallel programming, http://www.openmp.org

  2. Perf Wiki, https://perf.wiki.kernel.org

  3. SuiteSparse: a Suite of Sparse matrix packages, http://www.cise.ufl.edu/research/sparse/SuiteSparse/

  4. SuiteSparseQR: multithreaded multifrontal sparse QR factorization, http://www.cise.ufl.edu/research/sparse/SPQR/

  5. AMD: AMD Core Math Library, http://www.amd.com/acml/

  6. Amdahl, G.: Validity of the single processor approach to achieving large-scale computing capabilities. In: AFIPS Conference Proceedings, vol. 30, pp. 483–485 (1967), http://www-inst.eecs.berkeley.edu/~n252/paper/Amdahl.pdf

  7. Amestoy, P.R., Duff, I.S., Puglisi, C.: Multifrontal qr factorization in a multiprocessor environment. Numerical Linear Algebra with Applications 3(4), 275–300 (1996), http://dx.doi.org/10.1002/SICI1099-150199607/083:4275::AID-NLA833.0.CO2-7

  8. Intel: Intel 64 and IA-32 Architectures Software Developers Manual; Volume 3B: System Programming Guide, Part 2, http://www.intel.com/Assets/PDF/manual/253669.pdf

  9. Intel: Math Kernel Library, http://software.intel.com/en-us/articles/intel-mkl/

  10. Klug, T., Ott, M., Weidendorfer, J., Trinitis, C.: autopin automated optimization of thread-to-core pinning on multicore systems. In: Stenström, P. (ed.) Transactions on High-Performance Embedded Architectures and Compilers III. LNCS, vol. 6590, pp. 219–235. Springer, Heidelberg (2011), http://dx.doi.org/10.1007/978-3-642-19448-1_12

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  11. Liu, J.W.H.: The multifrontal method for sparse matrix solution: Theory and practice. SIAM Review 34(1), 82–109 (1992), http://link.aip.org/link/?SIR/34/82/1

    Article  MATH  Google Scholar 

  12. Matstoms, P.: Sparse linear least squares problems in optimization. Computational Optimization and Applications 7, 89–110 (1997), http://dx.doi.org/10.1023/A:1008680131271

    Article  MATH  Google Scholar 

  13. Tinney, W., Brandwajn, V., Chan, S.: Sparse vector methods. IEEE Transactions on Power Apparatus and Systems PAS 104(2), 295–301 (1985)

    Article  Google Scholar 

  14. Trinitis, C., Küstner, T., Weidendorfer, J., Smajic, J.: Sparse matrix operations on multi-core architectures. In: Malyshkin, V. (ed.) PaCT 2009. LNCS, vol. 5698, pp. 41–48. Springer, Heidelberg (2009), http://dx.doi.org/10.1007/978-3-642-03275-2_5

    Chapter  Google Scholar 

  15. Trinitis, C., Küstner, T., Weidendorfer, J., Smajic, J.: Sparse matrix operations on several multi-core architectures. The Journal of Supercomputing, 1–9 (2010), http://dx.doi.org/10.1007/s11227-010-0428-9

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Müller, T., Trinitis, C., Smajic, J. (2011). Cache Efficiency and Scalability on Multi-core Architectures. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2011. Lecture Notes in Computer Science, vol 6873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23178-0_8

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  • DOI: https://doi.org/10.1007/978-3-642-23178-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23177-3

  • Online ISBN: 978-3-642-23178-0

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