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
We expect that multiscale simulations will be one of the main high performance computing workloads i...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
We present a novel distributed memory Tridiagonal solver library, targeting large-scale systems base...
While parallel computers offer significant computational performance, it is generally necessary to e...
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...
The aim of this study is to devise an efficient and scalable computational procedure to solve the ma...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
We study the performance of three parallel algorithms and their hybrid variants for solving tridiago...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
While parallel computers offer significant computational performance, it is generally nec-essary to ...
A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems Rio Yokota...
We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulati...
Parallel computing a b s t r a c t A block tridiagonal matrix is factored with minimal fill-in using...
We expect that multiscale simulations will be one of the main high performance computing workloads i...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
We present a novel distributed memory Tridiagonal solver library, targeting large-scale systems base...
While parallel computers offer significant computational performance, it is generally necessary to e...
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...
The aim of this study is to devise an efficient and scalable computational procedure to solve the ma...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
We study the performance of three parallel algorithms and their hybrid variants for solving tridiago...
Tridiagonal solvers are important building blocks for a wide range of scientific applications that a...
While parallel computers offer significant computational performance, it is generally nec-essary to ...
A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems Rio Yokota...
We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulati...
Parallel computing a b s t r a c t A block tridiagonal matrix is factored with minimal fill-in using...
We expect that multiscale simulations will be one of the main high performance computing workloads i...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...