GHOST

Overview

GHOST is the “General, Hybrid, and Optimized Sparse Toolkit.”  It provides basic building blocks for computations with very large sparse or dense matrices. GHOST is being developed as part of the ESSEX project under the umbrella of the Priority Programme 1648: Software for Exascale Computing (SPPEXA) of the German Research Foundation (DFG). The library is able to deal with systems containing standard multicore CPUs, Nvidia GPGPUs, and Intel Xeon Phis, and supports heterogeneous parallelism across all three architectures in the same program. GHOST is running successfully on current post-petascale systems such as Oakforest-PACS at the University of Tokyo (Top500 #7 in June 2017) or Piz Daint at the Swiss National Supercomputing Center (CSCS) in Lugano (Top500 #3 in June 2017).

Open-Source: ✓
Main developer: Dominik Ernst (previously Dr. Moritz Kreutzer), HPC group @ FAU

Publications

  • A. Alvermann, A. Basermann, H.-J. Bungartz, C. Carbogno, D. Ernst, H. Fehske, Y. Futamura, M. Galgon, G. Hager, S. Huber, T. Huckle, A. Ida, A. Imakura, M. Kawai, S. Köcher, M. Kreutzer, P. Kus, B. Lang, H. Lederer, V. Manin, A. Marek,  K. Nakajima, L. Nemec, K. Reuter, M. Rippl, M. Röhrig-Zöllner, T. Sakurai, M. Scheffler, C. Scheurer, F. Shahzad, D. Simoes Brambila, J. Thies, and G. Wellein: Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects. Proc. EPASA 2018, Japan Journal of Industrial and Applied Mathematics, 36(2), 699-717, DOI: 10.1007/s13160-019-00360-8. Preprint: arXiv:1806.01036.
  • M. Kreutzer, G. Hager, D. Ernst, H. Fehske, A.R. Bishop, and G. Wellein: Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs. In: R. Yokota, M. Weiland, D. Keyes, and C. Trinitis (eds.): High Performance Computing: 33rd International Conference, ISC High Performance 2018, Frankfurt, Germany, June 24-28, 2018, Proceedings, Springer, Cham, LNCS 10876, ISBN 978-3-319-92040-5 (2018), 329-349. DOI: 10.1007/978-3-319-92040-5_17. ISC 2018 Hans Meuer Award Finalist.
  • M. Galgon, L. Krämer, B. Lang, A. Alvermann, H. Fehske, A. Pieper, G. Hager, M. Kreutzer, F. Shahzad, G. Wellein, A. Basermann, M. Röhrig-Zöllner, and J. Thies: Improved coefficients for polynomial filtering in ESSEX. In T. Sakurai, S.-L. Zhang, T. Imamura, Y. Yamamoto, Y. Kuramashi, and T. Hoshi (eds.), Eigenvalue Problems: Algorithms, Software and Applications, in Petascale Computing. Proc. EPASA 2015, Tsukuba, Japan, September 2015, volume 117 of LNCSE, pages 63-79. Springer International Publishing, 2017. DOI: 10.1007/978-3-319-62426-6_5
  • M. Kreutzer, J. Thies, M. Röhrig-Zöllner, A. Pieper, F. Shahzad, M. Galgon, A. Basermann, H. Fehske, G. Hager, and G. Wellein: GHOST: Building blocks for high performance sparse linear algebra on heterogeneous systems. International Journal of Parallel Programming (2016). DOI: 10.1007/s10766-016-0464-z. Preprint: arXiv:1507.08101
  • J. Thies, M. Galgon, F. Shahzad, A. Alvermann, M. Kreutzer, A. Pieper, M. Röhrig-Zöllner, A. Basermann, H. Fehske, G. Hager, B. Lang, and G. Wellein: Towards an Exascale Enabled Sparse Solver Repository. In: Software for Exascale Computing – SPPEXA 2013-2015, Volume 113 of the series Lecture Notes in Computational Science and Engineering, 295-316 (2016). DOI: 10.1007/978-3-319-40528-5_13. Preprint: lncs_CWPs-4.pdf
  • M. Kreutzer, J. Thies, A. Pieper, A. Alvermann, M. Galgon, M. Röhrig-Zöllner, F. Shahzad, A. Basermann, A. R. Bishop, H. Fehske, G. Hager, B. Lang, and G. Wellein: Performance Engineering and Energy Efficiency of Building Blocks for Large, Sparse Eigenvalue Computations on Heterogeneous Supercomputers. In: Software for Exascale Computing – SPPEXA 2013-2015, Volume 113 of the series Lecture Notes in Computational Science and Engineering, 317-338 (2016). DOI: 10.1007/978-3-319-40528-5_14
  • A. Alvermann, A. Basermann, H. Fehske, Martin Galgon, G. Hager, M. Kreutzer, L. Krämer, B. Lang, A. Pieper, M. Röhrig-Zöllner, F. Shahzad, J. Thies, and G. Wellein: ESSEX: Equipping Sparse Solvers for Exascale. In: L. Lopes et al. (Eds.): Euro-Par 2014 Workshops, Part II, LNCS 8806, 577-588 (2014). DOI: 10.1007/978-3-319-14313-2_49. Preprint
  • M. Kreutzer, G. Hager, G. Wellein, H. Fehske, and A. R. Bishop: A unified sparse matrix data format for efficient general sparse matrix-vector multiplication on modern processors with wide SIMD units. SIAM Journal on Scientific Computing 36(5), C401–C423 (2014). DOI: 10.1137/130930352, Preprint: arXiv:1307.6209, BibTeX

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