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Toward a modular precision ecosystem for high performance computing

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Toward a modular precision ecosystem for high performance computing

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Anzt, H.; Flegar, G.; Gruetzmacher, T.; Quintana-Orti, ES. (2019). Toward a modular precision ecosystem for high performance computing. International Journal of High Performance Computing Applications. 33(6):1069-1078. https://doi.org/10.1177/1094342019846547

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Título: Toward a modular precision ecosystem for high performance computing
Autor: Anzt, Hartwig Flegar, Goran Gruetzmacher, Thomas Quintana-Orti, Enrique S.
Entidad UPV: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] With the memory bandwidth of current computer architectures being significantly slower than the (floating point) arithmetic performance, many scientific computations only leverage a fraction of the computational power ...[+]
Palabras clave: Modular precision , Parallel numerical linear algebra , Jacobi method , PageRank , Conjugate gradient , Multicore processors , GPUs
Derechos de uso: Reserva de todos los derechos
Fuente:
International Journal of High Performance Computing Applications. (issn: 1094-3420 )
DOI: 10.1177/1094342019846547
Editorial:
SAGE Publications
Versión del editor: https://doi.org/10.1177/1094342019846547
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/732631/EU/Open transPREcision COMPuting/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-82972-R/ES/TECNICAS ALGORITMICAS PARA COMPUTACION DE ALTO RENDIMIENTO CONSCIENTE DEL CONSUMO ENERGETICO Y RESISTENTE A ERRORES/
info:eu-repo/grantAgreement/Helmholtz Association of German Research Centers//VH-NG-1241/
Agradecimientos:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Impuls und Vernetzungsfond of the Helmholtz Association ...[+]
Tipo: Artículo

References

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Buttari, A., Dongarra, J., Langou, J., Langou, J., Luszczek, P., & Kurzak, J. (2007). Mixed Precision Iterative Refinement Techniques for the Solution of Dense Linear Systems. The International Journal of High Performance Computing Applications, 21(4), 457-466. doi:10.1177/1094342007084026 [+]
Anzt, H., Dongarra, J., & Quintana-Ortí, E. S. (2015). Adaptive precision solvers for sparse linear systems. Proceedings of the 3rd International Workshop on Energy Efficient Supercomputing - E2SC ’15. doi:10.1145/2834800.2834802

Baboulin, M., Buttari, A., Dongarra, J., Kurzak, J., Langou, J., Langou, J., … Tomov, S. (2009). Accelerating scientific computations with mixed precision algorithms. Computer Physics Communications, 180(12), 2526-2533. doi:10.1016/j.cpc.2008.11.005

Buttari, A., Dongarra, J., Langou, J., Langou, J., Luszczek, P., & Kurzak, J. (2007). Mixed Precision Iterative Refinement Techniques for the Solution of Dense Linear Systems. The International Journal of High Performance Computing Applications, 21(4), 457-466. doi:10.1177/1094342007084026

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Göddeke, D., Strzodka, R., & Turek, S. (2007). Performance and accuracy of hardware-oriented native-, emulated- and mixed-precision solvers in FEM simulations. International Journal of Parallel, Emergent and Distributed Systems, 22(4), 221-256. doi:10.1080/17445760601122076

Grützmacher, T., & Anzt, H. (2018). A Modular Precision Format for Decoupling Arithmetic Format and Storage Format. Euro-Par 2018: Parallel Processing Workshops, 434-443. doi:10.1007/978-3-030-10549-5_34

Grutzmacher, T., Anzt, H., Scheidegger, F., & Quintana-Orti, E. S. (2018). High-Performance GPU Implementation of PageRank with Reduced Precision Based on Mantissa Segmentation. 2018 IEEE/ACM 8th Workshop on Irregular Applications: Architectures and Algorithms (IA3). doi:10.1109/ia3.2018.00015

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Saad, Y. (2003). Iterative Methods for Sparse Linear Systems. doi:10.1137/1.9780898718003

Strzodka, R., & Goddeke, D. (2006). Pipelined Mixed Precision Algorithms on FPGAs for Fast and Accurate PDE Solvers from Low Precision Components. 2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines. doi:10.1109/fccm.2006.57

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