Add to ORKGIn this paper, we deal with algorithmic issues on heterogeneous platforms. We concentrate on dense linear algebra kernels, such as matrix multiplication or LU decomposition. Block cyclic distribution techniques used in ScaLAPACK are no longer sufficient to balance the load among processors running at different speeds. The main result of this paper is to provide a static data distribution scheme that leads to an asymptotically perfect load balancing for LU decomposition, thereby providing solid foundations toward the design of a cluster-oriented version of ScaLAPACK
(eng) Implementing linear algebra kernels on distributed memory parallel computers raises the proble...
This paper presents and analyzes two different strategies of heterogeneous distribution of computati...
International audienceWe study the implementation of dense linear algebra computations, such as matr...
In this paper, we deal with algorithmic issues on heterogeneous platforms. We concentrate on dense l...
National audienceIn this paper, we deal with algorithmic issues on heterogeneous platforms. We conce...
International audienceThis paper discusses some algorithmic issues when computing with a heterogeneo...
This paper discusses some algorithmic issues when computing with a heterogeneous network of workstat...
This paper discusses the design and the implementation of the LU factorization routines included in ...
(eng) In this paper, we deal with redistribution issues for dense linear algebra kernels on heteroge...
In this paper, we deal with redistribution issues for dense linear algebra kernels on heterogeneous ...
International audienceLarge clusters and supercomputers are rapidly evolving and may be subject to r...
This paper describes the design of ScaLAPACK, a scalable software library for performing dense and b...
This paper presents some works on the LU factorization from the ScaLAPACK library. First, a complexi...
This paper describes the design and the implementation of parallel routines in the Heterogeneous Sca...
(eng) We study the implementation of dense linear algebra computations, such as matrix multiplicatio...
(eng) Implementing linear algebra kernels on distributed memory parallel computers raises the proble...
This paper presents and analyzes two different strategies of heterogeneous distribution of computati...
International audienceWe study the implementation of dense linear algebra computations, such as matr...
In this paper, we deal with algorithmic issues on heterogeneous platforms. We concentrate on dense l...
National audienceIn this paper, we deal with algorithmic issues on heterogeneous platforms. We conce...
International audienceThis paper discusses some algorithmic issues when computing with a heterogeneo...
This paper discusses some algorithmic issues when computing with a heterogeneous network of workstat...
This paper discusses the design and the implementation of the LU factorization routines included in ...
(eng) In this paper, we deal with redistribution issues for dense linear algebra kernels on heteroge...
In this paper, we deal with redistribution issues for dense linear algebra kernels on heterogeneous ...
International audienceLarge clusters and supercomputers are rapidly evolving and may be subject to r...
This paper describes the design of ScaLAPACK, a scalable software library for performing dense and b...
This paper presents some works on the LU factorization from the ScaLAPACK library. First, a complexi...
This paper describes the design and the implementation of parallel routines in the Heterogeneous Sca...
(eng) We study the implementation of dense linear algebra computations, such as matrix multiplicatio...
(eng) Implementing linear algebra kernels on distributed memory parallel computers raises the proble...
This paper presents and analyzes two different strategies of heterogeneous distribution of computati...
International audienceWe study the implementation of dense linear algebra computations, such as matr...