Ponència presentada al 2nd Workshop on Power-Aware Computing (PACO 2017) Ringberg Castle, Germany, July, 5-8 2017We investigate the eficiency of state-of-the-art multicore processors using a multi-threaded task-parallel implementation of the Conjugate Gradient (CG) method, accelerated with an incomplete LU (ILU) preconditioner. Concretely, we analyze multicore architectures with distinct designs and market targets to compare their parallel performance and energy eficiency
Graphics Processing Units (GPUs) exhibit significantly higher peak performance than conventional CPU...
We investigate the benefits that an energyaware implementation of the runtime in charge of the con...
We present specialized implementations of the preconditioned iterative linear system solver in ILUP...
Ponència presentada al 2nd Workshop on Power-Aware Computing (PACO 2017) Ringberg Castle, Germany, J...
We investigate the efficiency of state-of-the-art multicore processors using a multi-threaded task-p...
We analyze the efficiency of servers equipped with state-of-the-art general-purpose multicore proces...
We target the parallel solution of sparse linear systems via iterative Krylov subspace–based methods...
Ponència presentada al 2nd Workshop on Power-Aware Computing (PACO 2017) Ringberg Castle, Germany, J...
We analyze the energy-performance balance of a task-parallel computation of an ILU-based preconditio...
We analyze the energy-performance balance of a task-parallel computation of an ILU-based preconditio...
This is the pre-peer reviewed version of the following article: Energy‐aware strategies for task‐par...
We investigate the efficient iterative solution of large-scale sparse linear systems on shared-memor...
This is the pre-peer reviewed version of the following article: Energy‐aware strategies for task‐par...
Graphics Processing Units (GPUs) exhibit significantly higher peak performance than conventional CPU...
AbstractWe propose a parallel implementation of the Preconditioned Conjugate Gradient algorithm on a...
Graphics Processing Units (GPUs) exhibit significantly higher peak performance than conventional CPU...
We investigate the benefits that an energyaware implementation of the runtime in charge of the con...
We present specialized implementations of the preconditioned iterative linear system solver in ILUP...
Ponència presentada al 2nd Workshop on Power-Aware Computing (PACO 2017) Ringberg Castle, Germany, J...
We investigate the efficiency of state-of-the-art multicore processors using a multi-threaded task-p...
We analyze the efficiency of servers equipped with state-of-the-art general-purpose multicore proces...
We target the parallel solution of sparse linear systems via iterative Krylov subspace–based methods...
Ponència presentada al 2nd Workshop on Power-Aware Computing (PACO 2017) Ringberg Castle, Germany, J...
We analyze the energy-performance balance of a task-parallel computation of an ILU-based preconditio...
We analyze the energy-performance balance of a task-parallel computation of an ILU-based preconditio...
This is the pre-peer reviewed version of the following article: Energy‐aware strategies for task‐par...
We investigate the efficient iterative solution of large-scale sparse linear systems on shared-memor...
This is the pre-peer reviewed version of the following article: Energy‐aware strategies for task‐par...
Graphics Processing Units (GPUs) exhibit significantly higher peak performance than conventional CPU...
AbstractWe propose a parallel implementation of the Preconditioned Conjugate Gradient algorithm on a...
Graphics Processing Units (GPUs) exhibit significantly higher peak performance than conventional CPU...
We investigate the benefits that an energyaware implementation of the runtime in charge of the con...
We present specialized implementations of the preconditioned iterative linear system solver in ILUP...