PLASMA

The Parallel Linear Algebra for Scalable Multi-core Architectures (PLASMA) project aims to address the critical and highly disruptive situation that is facing the Linear Algebra and High Performance Computing community due to the introduction of multi-core architectures. PLASMA’s ultimate goal is to create software frameworks that enable programmers to simplify the process of developing applications that can achieve both high performance and portability across a range of new architectures. The development of programming models that enforce asynchronous, out of order scheduling of operations is the concept used as the basis for the definition of a scalable yet highly efficient software framework for Computational Linear Algebra applications.


References in zbMATH (referenced in 25 articles )

Showing results 1 to 20 of 25.
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  1. Abdelfattah, A.; Anzt, H.; Dongarra, J.; Gates, M.; Haidar, A.; Kurzak, J.; Luszczek, P.; Tomov, S.; Yamazaki, I.; YarKhan, A.: Linear algebra software for large-scale accelerated multicore computing (2016)
  2. Beliakov, Gleb; Matiyasevich, Yuri: A parallel algorithm for calculation of determinants and minors using arbitrary precision arithmetic (2016)
  3. Chiang, Nai-Yuan; Zavala, Victor M.: An inertia-free filter line-search algorithm for large-scale nonlinear programming (2016)
  4. Ghysels, Pieter; Li, Xiaoye S.; Rouet, François-Henry; Williams, Samuel; Napov, Artem: An efficient multicore implementation of a novel HSS-structured multifrontal solver using randomized sampling (2016)
  5. Michailidis, Panagiotis D.; Margaritis, Konstantinos G.: Scientific computations on multi-core systems using different programming frameworks (2016)
  6. Rupp, Karl; Tillet, Philippe; Rudolf, Florian; Weinbub, Josef; Morhammer, Andreas; Grasser, Tibor; Jüngel, Ansgar; Selberherr, Siegfried: ViennaCL-linear algebra library for multi- and many-core architectures (2016)
  7. Tillenius, Martin: Superglue: a shared memory framework using data versioning for dependency-aware task-based parallelization (2015)
  8. Ciznicki, Milosz; Kurowski, Krzysztof; Węglarz, Jan: Evaluation of selected resource allocation and scheduling methods in heterogeneous many-core processors and graphics processing units (2014)
  9. D’Azevedo, Eduardo; Hu, Zhiang; Su, Shi-Quan; Wong, Kwai: Solving a large scale radiosity problem on GPU-based parallel computers (2014)
  10. Schatz, Martin D.; Low, Tze Meng; van de Geijn, Robert A.; Kolda, Tamara G.: Exploiting symmetry in tensors for high performance: multiplication with symmetric tensors (2014)
  11. Ghysels, P.; Ashby, T.J.; Meerbergen, K.; Vanroose, W.: Hiding global communication latency in the GMRES algorithm on massively parallel machines (2013)
  12. Obrecht, Christian; Kuznik, Frédéric; Tourancheau, Bernard; Roux, Jean-Jacques: Multi-GPU implementation of the lattice Boltzmann method (2013)
  13. Bosilca, George; Bouteiller, Aurelien; Danalis, Anthony; Herault, Thomas; Lemarinier, Pierre; Dongarra, Jack: DAGuE: A generic distributed DAG engine for high performance computing (2012)
  14. Haidar, Azzam; Ltaief, Hatem; Dongarra, Jack: Toward a high performance tile divide and conquer algorithm for the dense symmetric eigenvalue problem (2012)
  15. Igual, Francisco D.; Chan, Ernie; Quintana-Ortí, Enrique S.; Quintana-Ortí, Gregorio; Van De Geijn, Robert A.; Van Zee, Field G.: The FLAME approach: from dense linear algebra algorithms to high-performance multi-accelerator implementations (2012)
  16. Vömel, Christof; Tomov, Stanimire; Dongarra, Jack: Divide and conquer on hybrid GPU-accelerated multicore systems (2012)
  17. Weinbub, Josef; Rupp, Karl; Selberherr, Siegfried: Towards distributed heterogenous high-performance computing with ViennaCL (2012)
  18. Agullo, Emmanuel; Bouwmeester, Henricus; Dongarra, Jack; Kurzak, Jakub; Langou, Julien; Rosenberg, Lee: Towards an efficient tile matrix inversion of symmetric positive definite matrices on multicore architectures (2011)
  19. Ltaief, Hatem; Tomov, Stanimire; Nath, Rajib; Du, Peng; Dongarra, Jack: A scalable high performant Cholesky factorization for multicore with GPU accelerators (2011)
  20. Mendiratta, Karan; Polizzi, Eric: A threaded SPIKE algorithm for solving general banded systems (2011)

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Further publications can be found at: http://icl.cs.utk.edu/plasma/pubs/index.html