Add to ORKGSPIKE::GPU is a solver developed in the Simulation Based Engineering Lab (SBEL) [1] to solve large banded and sparse linear systems on the GPU. This report contributes the performance comparison of the banded solver of SPIKE::GPU and Intel’s Math Ker-nel Library [2] on a large set of synthetic problems. The results of several numerical experiments indicate that when it is used in conjunction with large dense banded ma-trices, SPIKE::GPU is two to five times faster than the latest version of the MKL dense solver when the latter is run on the Haswell, Ivy Bridge, or Phi architectures
We have ported the numerical factorization and triangular solve phases of the sparse direct solver S...
AbstractNowadays, GPU computations are playing significant role in supercomputing technologies. This...
Graphical Processing Units (GPUs) have become more accessible peripheral devices with great computin...
The SPIKE algorithm [1, 2] is an efficient generic divide-and-conquer algorithm for solving banded s...
This contribution outlines an approach that draws on general purpose graphics processing unit (GPGPU...
With availability of large-scale parallel platforms comprised of tens-of-thousands of processors and...
Extended version of EuroGPU symposium article, in the International Conference on Parallel Computing...
GPU acceleration is the concept of accelerating the execution speed of an application by running it ...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...
Simulations are indispensable for engineering. They make it possible that one can perform fa...
Abstract: If multicore is a disruptive technology, try to imagine hybrid multicore systems enhanced ...
Graphical processing units (GPUs) have recently attracted attention for scientific applications such...
We consider a fast, robust and scalable solver using graphic processing units (GPU) as accelerators ...
In the recent years, the graphics processing unit (GPU) has emerged as a popular platform for perfor...
Solving diagonally dominant tridiagonal linear systems is a common problem in scientific high-perfor...
We have ported the numerical factorization and triangular solve phases of the sparse direct solver S...
AbstractNowadays, GPU computations are playing significant role in supercomputing technologies. This...
Graphical Processing Units (GPUs) have become more accessible peripheral devices with great computin...
The SPIKE algorithm [1, 2] is an efficient generic divide-and-conquer algorithm for solving banded s...
This contribution outlines an approach that draws on general purpose graphics processing unit (GPGPU...
With availability of large-scale parallel platforms comprised of tens-of-thousands of processors and...
Extended version of EuroGPU symposium article, in the International Conference on Parallel Computing...
GPU acceleration is the concept of accelerating the execution speed of an application by running it ...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...
Simulations are indispensable for engineering. They make it possible that one can perform fa...
Abstract: If multicore is a disruptive technology, try to imagine hybrid multicore systems enhanced ...
Graphical processing units (GPUs) have recently attracted attention for scientific applications such...
We consider a fast, robust and scalable solver using graphic processing units (GPU) as accelerators ...
In the recent years, the graphics processing unit (GPU) has emerged as a popular platform for perfor...
Solving diagonally dominant tridiagonal linear systems is a common problem in scientific high-perfor...
We have ported the numerical factorization and triangular solve phases of the sparse direct solver S...
AbstractNowadays, GPU computations are playing significant role in supercomputing technologies. This...
Graphical Processing Units (GPUs) have become more accessible peripheral devices with great computin...