Add to ORKGAbstract. We pursue the scalable parallel implementation of the factor-ization of band matrices with medium to large bandwidth targeting SMP and multi-core architectures. Our approach decomposes the computation into a large number of fine-grained operations exposing a higher degree of parallelism. The SuperMatrix run-time system allows an out-of-order scheduling of operations that is transparent to the programmer. Exper-imental results for the Cholesky factorization of band matrices on two parallel platforms with sixteen processors demonstrate the scalability of the solution
This paper is concerned with parallel algorithms for matrix factorization on distributed-memory, mes...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
This paper discusses the scalability of Cholesky, LU, and QR factorization routines on MIMD distribu...
We pursue the scalable parallel implementation of the factor- ization of band matrices with medium ...
The bottleneck of most data analyzing systems, signal processing systems, and intensive computing sy...
The objective of this paper is to extend, in the context of multicore architectures, the concepts of...
Abstract. The objective of this paper is to extend, in the context of multicore architectures, the c...
Abstract. A style for programming problems from matrix algebra is developed with a familiar example ...
We develop an algorithm for computing the symbolic and numeric Cholesky factorization of a large sp...
We discuss the high-performance parallel implementation and execution of dense linear algebra matrix...
Abstract: This paper presents a 7-step, semi-systematic approach for designing and implementing para...
We describe a parallel algorithm for finding the Cholesky factorization of a sparse symmetric posit...
In this paper, we investigate how to exploit task-parallelism during the execution of the Cholesky f...
Ecient execution of numerical algorithms requires adapting the code to the underlying execution plat...
AbstractA parallel algorithm is developed for Cholesky factorization on a shared-memory multiprocess...
This paper is concerned with parallel algorithms for matrix factorization on distributed-memory, mes...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
This paper discusses the scalability of Cholesky, LU, and QR factorization routines on MIMD distribu...
We pursue the scalable parallel implementation of the factor- ization of band matrices with medium ...
The bottleneck of most data analyzing systems, signal processing systems, and intensive computing sy...
The objective of this paper is to extend, in the context of multicore architectures, the concepts of...
Abstract. The objective of this paper is to extend, in the context of multicore architectures, the c...
Abstract. A style for programming problems from matrix algebra is developed with a familiar example ...
We develop an algorithm for computing the symbolic and numeric Cholesky factorization of a large sp...
We discuss the high-performance parallel implementation and execution of dense linear algebra matrix...
Abstract: This paper presents a 7-step, semi-systematic approach for designing and implementing para...
We describe a parallel algorithm for finding the Cholesky factorization of a sparse symmetric posit...
In this paper, we investigate how to exploit task-parallelism during the execution of the Cholesky f...
Ecient execution of numerical algorithms requires adapting the code to the underlying execution plat...
AbstractA parallel algorithm is developed for Cholesky factorization on a shared-memory multiprocess...
This paper is concerned with parallel algorithms for matrix factorization on distributed-memory, mes...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
This paper discusses the scalability of Cholesky, LU, and QR factorization routines on MIMD distribu...