GHOST: Building Blocks for High Performance Sparse Linear Algebra on Heterogeneous Systems

Journal article
(Original article)

Publication Details

Author(s): Kreutzer M, Thies J, Röhrig-Zöllner M, Pieper A, Shahzad F, Galgon M, Basermann A, Fehske H, Hager G, Wellein G
Journal: International Journal of Parallel Programming
Publisher: Springer New York LLC
Publication year: 2016
Pages range: 1-27
ISSN: 0885-7458


While many of the architectural details of future exascale-class high performance computer systems are still a matter of intense research, there appears to be a general consensus that they will be strongly heterogeneous, featuring “standard” as well as “accelerated” resources. Today, such resources are available as multicore processors, graphics processing units (GPUs), and other accelerators such as the Intel Xeon Phi. Any software infrastructure that claims usefulness for such environments must be able to meet their inherent challenges: massive multi-level parallelism, topology, asynchronicity, and abstraction. The “General, Hybrid, and Optimized Sparse Toolkit” (GHOST) is a collection of building blocks that targets algorithms dealing with sparse matrix representations on current and future large-scale systems. It implements the “MPI+X” paradigm, has a pure C interface, and provides hybrid-parallel numerical kernels, intelligent resource management, and truly heterogeneous parallelism for multicore CPUs, Nvidia GPUs, and the Intel Xeon Phi. We describe the details of its design with respect to the challenges posed by modern heterogeneous supercomputers and recent algorithmic developments. Implementation details which are indispensable for achieving high efficiency are pointed out and their necessity is justified by performance measurements or predictions based on performance models. We also provide instructions on how to make use of GHOST in existing software packages, together with a case study which demonstrates the applicability and performance of GHOST as a component within a larger software stack. The library code and several applications are available as open source.

FAU Authors / FAU Editors

Hager, Georg Dr.
Regionales Rechenzentrum Erlangen (RRZE)
Kreutzer, Moritz
Regionales Rechenzentrum Erlangen (RRZE)
Pieper, Andreas
Regionales Rechenzentrum Erlangen (RRZE)
Shahzad, Faisal
Regionales Rechenzentrum Erlangen (RRZE)
Wellein, Gerhard Prof. Dr.
Professur für Höchstleistungsrechnen

External institutions with authors

Bergische Universität Wuppertal
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Universität Greifswald

How to cite

Kreutzer, M., Thies, J., Röhrig-Zöllner, M., Pieper, A., Shahzad, F., Galgon, M.,... Wellein, G. (2016). GHOST: Building Blocks for High Performance Sparse Linear Algebra on Heterogeneous Systems. International Journal of Parallel Programming, 1-27.

Kreutzer, Moritz, et al. "GHOST: Building Blocks for High Performance Sparse Linear Algebra on Heterogeneous Systems." International Journal of Parallel Programming (2016): 1-27.


Last updated on 2018-11-11 at 13:50