Listar por tema "Sparse linear systems"
Mostrando ítems 1-5 de 5
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Accelerating the task/data-parallel version of ILUPACK’s BiCG in multi-CPU/GPU configurations
Elsevier (2019)ILUPACK is a valuable tool for the solution of sparse linear systems via iterative Krylov subspace-based methods. Its relevance for the solution of real problems has motivated several efforts to enhance its performance on ... -
Assessing the impact of the CPU power-saving modes on the task-parallel solution of sparse linear systems
Springer US (2014)We investigate the benefits that an energyaware implementation of the runtime in charge of the concurrent execution of ILUPACK —a sophisticated preconditioned iterative solver for sparse linear systems— produces on the ... -
Exploiting Task and Data Parallelism in ILUPACK's Preconditioned CG Solver on NUMA Architectures and Many-core Accelerators
Elsevier (2016-05)We present specialized implementations of the preconditioned iterative linear system solver in ILUPACK for Non-Uniform Memory Access (NUMA) platforms and many-core hardware co-processors based on the Intel Xeon Phi and ... -
Tuning stationary iterative solvers for fault resilience
ACM. Association for Computing Machinery (2015)As the transistor’s feature size decreases following Moore’s Law, hardware will become more prone to permanent, intermittent, and transient errors, increasing the number of failures experienced by applications, and ... -
Variable-size batched Gauss–Jordan elimination for block-Jacobi preconditioning on graphics processors
Elsevier (2019)In this work, we address the efficient realization of block-Jacobi preconditioning on graphics processing units (GPUs). This task requires the solution of a collection of small and independent linear systems. To fully ...