A new parallel solver based on SPIKE-TA algorithm has been developed using OpenMP API for solving diagonally-dominant banded linear systems on shared memory architectures. The results of the numerical experiments carried out for different test cases demonstrate high-performance and scalability on current multi-core platforms and highlight the time savings that SPIKE-TA OpenMP offers in comparison to the LAPACK BLAS-threaded LU model. By exploiting algorithmic parallelism in addition to threaded implementation, we obtain greater speed-ups in contrast to the threaded versions of sequential algorithms. For non-diagonally dominant systems, we implement the SPIKE-RL scheme and a new Spike-calling-Spike (SCS) scheme using OpenMP. The ti...
The emergence of multicore architectures and highly scalable platforms motivates the development of ...
Generic simulation code for spiking neuronal networks spends the major part of the time in the phase...
Algorithmic skeletons simplify software development: they abstract typical patterns of parallelism a...
SPIKE is a parallel algorithm to solve block tridiagonal matrices. In this work, two useful improvem...
The SPIKE algorithm [1, 2] is an efficient generic divide-and-conquer algorithm for solving banded s...
Tridiagonal diagonally dominant linear systems arise in many scientific and engineering applications...
Solving linear systems is an important problem for scientific computing. Exploiting parallelism is e...
With availability of large-scale parallel platforms comprised of tens-of-thousands of processors and...
We propose a parallel sparse triangular linear system solver based on the Spike algorithm. Sparse tr...
The truncated SPIKE algorithm is a parallel solver for linear systems which are banded and strictly ...
The explicit Spike algorithm applies to narrow banded linear systems which are strictly diagonally d...
International audienceWe introduce shared-memory parallelism in a parallel distributed-memory solver...
ii This paper describes the SPIKE algorithm for solving large banded linear systems using a divide-a...
The emergence of multicore architectures and highly scalable platforms motivates the development of ...
This contribution outlines an approach that draws on general purpose graphics processing unit (GPGPU...
The emergence of multicore architectures and highly scalable platforms motivates the development of ...
Generic simulation code for spiking neuronal networks spends the major part of the time in the phase...
Algorithmic skeletons simplify software development: they abstract typical patterns of parallelism a...
SPIKE is a parallel algorithm to solve block tridiagonal matrices. In this work, two useful improvem...
The SPIKE algorithm [1, 2] is an efficient generic divide-and-conquer algorithm for solving banded s...
Tridiagonal diagonally dominant linear systems arise in many scientific and engineering applications...
Solving linear systems is an important problem for scientific computing. Exploiting parallelism is e...
With availability of large-scale parallel platforms comprised of tens-of-thousands of processors and...
We propose a parallel sparse triangular linear system solver based on the Spike algorithm. Sparse tr...
The truncated SPIKE algorithm is a parallel solver for linear systems which are banded and strictly ...
The explicit Spike algorithm applies to narrow banded linear systems which are strictly diagonally d...
International audienceWe introduce shared-memory parallelism in a parallel distributed-memory solver...
ii This paper describes the SPIKE algorithm for solving large banded linear systems using a divide-a...
The emergence of multicore architectures and highly scalable platforms motivates the development of ...
This contribution outlines an approach that draws on general purpose graphics processing unit (GPGPU...
The emergence of multicore architectures and highly scalable platforms motivates the development of ...
Generic simulation code for spiking neuronal networks spends the major part of the time in the phase...
Algorithmic skeletons simplify software development: they abstract typical patterns of parallelism a...