We present a novel distributed memory Tridiagonal solver library, targeting large-scale systems based on modern multi-core and many-core processor architectures. The library uses methods based on both approximate and exact algorithms. Performance comparisons with the state-of-the-art, using both a large Cray EX system and a GPU cluster show the algorithmic trade-offs required at increasing machine scale to achieve good performance, particularly considering the advent of exascale systems
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
[Abstract] Current Graphics Processing Units (GPUs) are capable of obtaining high computational perf...
A new high-performance general-purpose graphics processing unit (GPGPU) computational fluid dynamics...
We present a novel distributed memory Tridiagonal solver library, targeting large-scale systems base...
We study the performance of three parallel algorithms and their hybrid variants for solving tridiago...
Tridiagonal diagonally dominant linear systems arise in many scientific and engineering applications...
Engineering, scientific, and financial applications often require the simultaneous solution of a lar...
While parallel computers offer significant computational performance, it is generally necessary to e...
We present a multi-stage method for solving large tridiagonal systems on the GPU. Previously large t...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
The aim of this study is to devise an efficient and scalable computational procedure to solve the ma...
A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems Rio Yokota...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
Compact finite difference schemes are widely used in the direct numerical simulation of fluid flows ...
2011-07-13The advent of multi-core/many-core paradigm has provided unprecedented computing power, an...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
[Abstract] Current Graphics Processing Units (GPUs) are capable of obtaining high computational perf...
A new high-performance general-purpose graphics processing unit (GPGPU) computational fluid dynamics...
We present a novel distributed memory Tridiagonal solver library, targeting large-scale systems base...
We study the performance of three parallel algorithms and their hybrid variants for solving tridiago...
Tridiagonal diagonally dominant linear systems arise in many scientific and engineering applications...
Engineering, scientific, and financial applications often require the simultaneous solution of a lar...
While parallel computers offer significant computational performance, it is generally necessary to e...
We present a multi-stage method for solving large tridiagonal systems on the GPU. Previously large t...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
The aim of this study is to devise an efficient and scalable computational procedure to solve the ma...
A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems Rio Yokota...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
Compact finite difference schemes are widely used in the direct numerical simulation of fluid flows ...
2011-07-13The advent of multi-core/many-core paradigm has provided unprecedented computing power, an...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
[Abstract] Current Graphics Processing Units (GPUs) are capable of obtaining high computational perf...
A new high-performance general-purpose graphics processing unit (GPGPU) computational fluid dynamics...