DDS: integrating data analytics transformations in task-based workflows [version 2; peer review: 1 approved, 2 approved with reservations]

Autor: Rosa M. Badia, Javier Alvarez, Jorge Ejarque, Nihad Mammadli

Publikováno v: Open Research Europe, Vol 2 (2023)

High-performance data analytics (HPDA) is a current trend in e-science research that aims to integrate traditional HPC with recent data analytic frameworks. Most of the work done in this field has focused on improving data analytic frameworks by impl

Externí odkaz: https://doaj.org/article/828c00dc8e224da3be72d91b81ad4851

DDS: integrating data analytics transformations in task-based workflows [version 1; peer review: 1 approved, 2 approved with reservations]

Autor: Rosa M. Badia, Javier Alvarez, Jorge Ejarque, Nihad Mammadli

Publikováno v: Open Research Europe, Vol 2 (2022)

High-performance data analytics (HPDA) is a current trend in e-science research that aims to integrate traditional HPC with recent data analytic frameworks. Most of the work done in this field has focused on improving data analytic frameworks by impl

Externí odkaz: https://doaj.org/article/64fe5bd34d6a4e19ab6b0d841f96f1c8

On the Arithmetic Intensity of Distributed-Memory Dense Matrix Multiplication Involving a Symmetric Input Matrix (SYMM)

Autor: Agullo, Emmanuel, Buttari, Alfredo, Coulaud, Olivier, Eyraud-Dubois, Lionel, Faverge, Mathieu, Franc, Alain, Guermouche, Abdou, Jego, Antoine, Peressoni, Romain, Pruvost, Florent

Publikováno v: International Parallel and Distributed Processing Symposium
IPDPS 2023-37th International Parallel and Distributed Processing Symposium
IPDPS 2023-37th International Parallel and Distributed Processing Symposium, IEEE, May 2023, St. Petersburg, FL, United States. à paraître

International audience; Dense matrix multiplication involving a symmetric input matrix (SYMM) is implemented in reference distributed-memory codes with the same data distribution as its general analogue (GEMM). We show that, when the symmetric matrix

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::75fb8b0fa4d2c7380e6b27af586006c1
https://inria.hal.science/hal-04093162

Task-based parallel programming for scalable matrix product algorithms

Autor: Agullo, Emmanuel, Buttari, Alfredo, Guermouche, Abdou, Herrmann, Julien, Jego, Antoine

Publikováno v: ACM Transactions on Mathematical Software
ACM Transactions on Mathematical Software, 2023, ⟨10.1145/3583560⟩

International audience; Task-based programming models have succeeded in gaining the interest of the high-performance mathematical software community because they relieve part of the burden of developing and implementing distributed-memory parallel al

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b446e450a7b1a93af595e041216080d
https://doi.org/10.1145/3583560

Storage-heterogeneity aware task-based programming models to optimize I/O intensive applications

Autor: Rosa M Badia, Jorge Ejarque, Hatem Elshazly

Publikováno v: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Task-based programming models have enabled the optimized execution of the computation workloads of applications. These programming models can take advantage of large-scale distributed infrastructures by allowing the parallel and distributed execution

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::768b987b5b4fb3f81f1e47f76886b36f
https://hdl.handle.net/2117/367747