We describe an efficient and innovative parallel tiled algorithm for solving symmetric indefinite systems on multicore architectures. This solver avoids pivoting by using a multiplicative preconditioning based on symmetric randomization. This randomization prevents the communication overhead due to pivoting, is computationally inexpensive and requires very little storage. Following randomization, a tiled LDLT factorization is used that reduces synchronization by using static or dynamic scheduling. We compare Gflop/s performance of our solver with other types of factorizations on a current multicore machine and we provide tests on accuracy using LAPACK test cases.Nous décrivons un algorithme parallèle par pavage efficace et innovant pour rés...
The objective of this paper is to extend and redesign the block matrix reduction applied for the fam...
Abstract. This paper discusses new pivoting factorization methods for solving sparse symmetric inden...
Ponència presentada al Euro-Par 2016: Parallel Processing Workshops pp 121–133.The solution of spars...
We describe an efficient and innovative parallel tiled algorithm for solving symmetric indefinite sy...
International audienceRandomized algorithms are gaining ground in high-performance computing applica...
Randomized algorithms are gaining ground in high-performance computing applications as they have the...
International audienceThis paper studies the performance of different algorithms for solving a dense...
International audienceWe study the performance of dense symmetric indefinite factorizations (Bunch-K...
The increasing number of cores in modern architectures requires the development of new algorithms as...
This paper describes the design, implementation and performance of a parallel direct dense symmetric...
This paper describes the design, implementation and performance of parallel direct dense symmetric...
This paper illustrates how the communication due to pivoting in the solution of symmetric indefinite...
The process of factorizing a symmetric matrix using the Cholesky (LLT ) or indefinite (LDLT ) factor...
In this PhD thesis, we study algorithms and implementations to accelerate the solution of dense line...
International audienceThis paper focuses on the resolution of a large number of small symmetric line...
The objective of this paper is to extend and redesign the block matrix reduction applied for the fam...
Abstract. This paper discusses new pivoting factorization methods for solving sparse symmetric inden...
Ponència presentada al Euro-Par 2016: Parallel Processing Workshops pp 121–133.The solution of spars...
We describe an efficient and innovative parallel tiled algorithm for solving symmetric indefinite sy...
International audienceRandomized algorithms are gaining ground in high-performance computing applica...
Randomized algorithms are gaining ground in high-performance computing applications as they have the...
International audienceThis paper studies the performance of different algorithms for solving a dense...
International audienceWe study the performance of dense symmetric indefinite factorizations (Bunch-K...
The increasing number of cores in modern architectures requires the development of new algorithms as...
This paper describes the design, implementation and performance of a parallel direct dense symmetric...
This paper describes the design, implementation and performance of parallel direct dense symmetric...
This paper illustrates how the communication due to pivoting in the solution of symmetric indefinite...
The process of factorizing a symmetric matrix using the Cholesky (LLT ) or indefinite (LDLT ) factor...
In this PhD thesis, we study algorithms and implementations to accelerate the solution of dense line...
International audienceThis paper focuses on the resolution of a large number of small symmetric line...
The objective of this paper is to extend and redesign the block matrix reduction applied for the fam...
Abstract. This paper discusses new pivoting factorization methods for solving sparse symmetric inden...
Ponència presentada al Euro-Par 2016: Parallel Processing Workshops pp 121–133.The solution of spars...