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- research-articleNovember 2022
Addressing irregular patterns of matrix computations on GPUs and their impact on applications powered by sparse direct solvers
SC '22: Proceedings of the International Conference on High Performance Computing, Networking, Storage and AnalysisNovember 2022, Article No.: 26, pp 1–14Many scientific applications rely on sparse direct solvers for their numerical robustness. However, performance optimization for these solvers remains a challenging task, especially on GPUs. This is due to workloads of small dense matrices that are ...
- research-articleJune 2021
A Set of Batched Basic Linear Algebra Subprograms and LAPACK Routines
- Ahmad Abdelfattah,
- Timothy Costa,
- Jack Dongarra,
- Mark Gates,
- Azzam Haidar,
- Sven Hammarling,
- Nicholas J. Higham,
- Jakub Kurzak,
- Piotr Luszczek,
- Stanimire Tomov,
- Mawussi Zounon
ACM Transactions on Mathematical Software (TOMS), Volume 47, Issue 3September 2021, Article No.: 21, pp 1–23https://doi.org/10.1145/3431921This article describes a standard API for a set of Batched Basic Linear Algebra Subprograms (Batched BLAS or BBLAS). The focus is on many independent BLAS operations on small matrices that are grouped together and processed by a single routine, called a ...
- research-articleAugust 2019
Massively Parallel Automated Software Tuning
ICPP '19: Proceedings of the 48th International Conference on Parallel ProcessingAugust 2019, Article No.: 92, pp 1–10https://doi.org/10.1145/3337821.3337908This article presents an implementation of a distributed autotuning engine developed as part of the Bench-testing OpenN Software Autotuning Infrastructure project. The system is geared towards performance optimization of computational kernels for ...
- research-articleJune 2017
Novel HPC techniques to batch execution of many variable size BLAS computations on GPUs
ICS '17: Proceedings of the International Conference on SupercomputingJune 2017, Article No.: 5, pp 1–10https://doi.org/10.1145/3079079.3079103This paper presents a software framework for solving large numbers of relatively small matrix problems using GPUs. Our approach combines novel and existing HPC techniques to methodically apply performance analysis, kernel design, low-level optimizations,...
- research-articleMay 2016
KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators
ACM Transactions on Mathematical Software (TOMS), Volume 42, Issue 3June 2016, Article No.: 18, pp 1–31https://doi.org/10.1145/2818311KBLAS is an open-source, high-performance library that provides optimized kernels for a subset of Level 2 BLAS functionalities on CUDA-enabled GPUs. Since performance of dense matrix-vector multiplication is hindered by the overhead of memory accesses, ...
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- research-articleNovember 2014
Pipelining computational stages of the tomographic reconstructor for multi-object adaptive optics on a multi-GPU system
- Ali Charara,
- Hatem Ltaief,
- Damien Gratadour,
- David Keyes,
- Arnaud Sevin,
- Ahmad Abdelfattah,
- Eric Gendron,
- Carine Morel,
- Fabrice Vidal
SC '14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and AnalysisNovember 2014, pp 262–273https://doi.org/10.1109/SC.2014.27The European Extremely Large Telescope project (E-ELT) is one of Europe's highest priorities in ground-based astronomy. ELTs are built on top of a variety of highly sensitive and critical astronomical instruments. In particular, a new instrument called ...
