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Pipelined Iterative Solvers with Kernel Fusion for Graphics Processing Units
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/pamm.201210004openalex-snapshot
Preconditioned Block‐Iterative Methods on GPUs
inferredcites →https://doi.org/10.1002/pamm.201210314openalex-snapshot
SPAI Preconditioners for HPC Applications
inferredcites →https://doi.org/10.1007/978-1-4615-5205-5_15openalex-snapshot
Electromagnetic Scattering with the Boundary Integral Method on MIMD Systems
inferredcites →https://doi.org/10.1007/978-3-642-55224-3_52openalex-snapshot
Performance Evaluation of Sparse Matrix Multiplication Kernels on Intel Xeon Phi
inferredcites →https://doi.org/10.1007/b97218openalex-snapshot
Parallel Processing and Applied Mathematics, 5th International Conference, PPAM 2003, Czestochowa, Poland, September 7-10, 2003. Revised Papers
inferredcites →https://doi.org/10.1007/s11227-012-0825-3openalex-snapshot
GPU-accelerated preconditioned iterative linear solvers
inferredcites →https://doi.org/10.1016/0010-4655(85)90014-1openalex-snapshot
A modified conjugate gradient solver for very large systems
inferredcites →https://doi.org/10.1016/0377-0427(89)90045-9openalex-snapshot
s-step iterative methods for symmetric linear systems
inferredcites →https://doi.org/10.1016/j.camwa.2014.08.022openalex-snapshot
A GPU accelerated aggregation algebraic multigrid method
inferredcites →https://doi.org/10.1016/j.cpc.2010.12.052openalex-snapshot
Swan: A tool for porting CUDA programs to OpenCL
inferredcites →https://doi.org/10.1016/j.cpc.2011.02.013openalex-snapshot
Biomolecular electrostatics using a fast multipole BEM on up to 512 gpus and a billion unknowns
inferredcites →https://doi.org/10.1016/j.jpdc.2008.05.008openalex-snapshot
Algorithmic performance studies on graphics processing units
inferredcites →https://doi.org/10.1016/j.parco.2013.06.001openalex-snapshot
Hiding global synchronization latency in the preconditioned Conjugate Gradient algorithm
inferredcites →https://doi.org/10.1016/j.procs.2010.04.024openalex-snapshot
The reordered BiCGStab method for distributed memory computer systems
inferredcites →https://doi.org/10.1063/1.4825816openalex-snapshot
A note on the GPU acceleration of eigenvalue computations
inferredcites →https://doi.org/10.1086/450439openalex-snapshot
A Note on the Sources and Uses of Funds in Thai Agriculture
inferredcites →https://doi.org/10.1109/fccm.2006.57openalex-snapshot
Pipelined Mixed Precision Algorithms on FPGAs for Fast and Accurate PDE Solvers from Low Precision Components
inferredcites →https://doi.org/10.1109/icapp.2002.1173595openalex-snapshot
The improved BiCGStab method for large and sparse unsymmetric linear systems on parallel distributed memory architectures
inferredcites →https://doi.org/10.1109/icpads.2011.48openalex-snapshot
CU2CL: A CUDA-to-OpenCL Translator for Multi- and Many-Core Architectures
inferredcites →https://doi.org/10.1109/icpp.2011.45openalex-snapshot
A Comprehensive Performance Comparison of CUDA and OpenCL
inferredcites →https://doi.org/10.1109/icpp.2013.41openalex-snapshot
Reformulated Conjugate Gradient for the Energy-Aware Solution of Linear Systems on GPUs
inferredcites →https://doi.org/10.1109/ipdps.2014.48openalex-snapshot
Improving the Performance of CA-GMRES on Multicores with Multiple GPUs
inferredcites →https://doi.org/10.1109/ipdpsw.2013.26openalex-snapshot
Scheduling a Parallel Sparse Direct Solver to Multiple GPUs
inferredcites →https://doi.org/10.1109/ipdpsw.2014.107openalex-snapshot
Optimizing Krylov Subspace Solvers on Graphics Processing Units
inferredcites →https://doi.org/10.1109/sc.2014.68openalex-snapshot
Efficient Sparse Matrix-Vector Multiplication on GPUs Using the CSR Storage Format
inferredcites →https://doi.org/10.1109/sc.2014.69openalex-snapshot
Fast Sparse Matrix-Vector Multiplication on GPUs for Graph Applications
inferredcites →https://doi.org/10.1109/tmag.2013.2283099openalex-snapshot
GPU Acceleration of Algebraic Multigrid Preconditioners for Discrete Elliptic Field Problems
inferredcites →https://doi.org/10.1109/tpds.2012.286openalex-snapshot
Parallel Sparse Approximate Inverse Preconditioning on Graphic Processing Units
inferredcites →https://doi.org/10.1137/0906059openalex-snapshot
Practical Use of Polynomial Preconditionings for the Conjugate Gradient Method
inferredcites →https://doi.org/10.1137/0907058openalex-snapshot
GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems
inferredcites →https://doi.org/10.1137/0913035openalex-snapshot
Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems
inferredcites →https://doi.org/10.1137/1.9780898718003openalex-snapshot
Iterative Methods for Sparse Linear Systems
inferredcites →https://doi.org/10.1137/110838844openalex-snapshot
Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods
inferredcites →https://doi.org/10.1137/12086563xopenalex-snapshot
Hiding Global Communication Latency in the GMRES Algorithm on Massively Parallel Machines
inferredcites →https://doi.org/10.1137/130930352openalex-snapshot
A Unified Sparse Matrix Data Format for Efficient General Sparse Matrix-Vector Multiplication on Modern Processors with Wide SIMD Units
inferredcites →https://doi.org/10.1145/1365490.1365500openalex-snapshot
Scalable Parallel Programming with CUDA
inferredcites →https://doi.org/10.1145/1401132.1401152openalex-snapshot
Scalable parallel programming with CUDA
inferredcites →https://doi.org/10.1145/1654059.1654078openalex-snapshot
Implementing sparse matrix-vector multiplication on throughput-oriented processors
inferredcites →https://doi.org/10.1145/1815961.1816021openalex-snapshot
Debunking the 100X GPU vs. CPU myth
inferredcites →https://doi.org/10.1145/2464996.2465013openalex-snapshot
Efficient sparse matrix-vector multiplication on x86-based many-core processors
inferredcites →https://doi.org/10.48550/arxiv.1005.2581openalex-snapshot
A Performance Comparison of CUDA and OpenCL
inferredcites →https://doi.org/10.5555/2338816.2338818openalex-snapshot
A comparison of algebraic multigrid preconditioners using graphics processing units and multi-core central processing units
inferredcites →https://doi.org/10.5555/2338816.2338829openalex-snapshot
Sparse approximate inverse preconditioners for iterative solvers on GPUs
inferredcites →https://doi.org/10.6028/jres.049.044openalex-snapshot
Methods of conjugate gradients for solving linear systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.3820openalex-snapshot
A stochastic performance model for pipelined Krylov methods
inferred← citeshttps://doi.org/10.1007/s00607-020-00827-4openalex-snapshot
GPU-based matrix-free finite element solver exploiting symmetry of elemental matrices
inferred← citeshttps://doi.org/10.1007/s10766-016-0464-zopenalex-snapshot
GHOST: Building Blocks for High Performance Sparse Linear Algebra on Heterogeneous Systems
inferred← citeshttps://doi.org/10.1016/j.camwa.2019.11.025openalex-snapshot
Revisiting performance of BiCGStab methods for solving systems with multiple right-hand sides
inferred← citeshttps://doi.org/10.1016/j.future.2019.07.075openalex-snapshot
Improving locality of explicit one-step methods on GPUs by tiling across stages and time steps
inferred← citeshttps://doi.org/10.1016/j.parco.2017.05.006openalex-snapshot
Preconditioned Krylov solvers on GPUs
inferred← citeshttps://doi.org/10.1016/j.parco.2017.11.006openalex-snapshot
MPI-CUDA parallel linear solvers for block-tridiagonal matrices in the context of SLEPc’s eigensolvers
inferred← citeshttps://doi.org/10.1109/cahpc.2018.8645892openalex-snapshot
Exploiting Limited Access Distance for Kernel Fusion Across the Stages of Explicit One-Step Methods on GPUs
inferred← citeshttps://doi.org/10.1109/sbac-pad.2015.29openalex-snapshot
OpenCL Kernel Fusion for GPU, Xeon Phi and CPU
inferred← citeshttps://doi.org/10.1109/sc41406.2024.00064openalex-snapshot
Mille-feuille: A Tile-Grained Mixed Precision Single-Kernel Conjugate Gradient Solver on GPUs
inferred← citeshttps://doi.org/10.1137/15m1026419openalex-snapshot
ViennaCL---Linear Algebra Library for Multi- and Many-Core Architectures
inferred← citeshttps://doi.org/10.1177/10943420221100262openalex-snapshot
Matrix-free approaches for GPU acceleration of a high-order finite element hydrodynamics application using MFEM, Umpire, and RAJA
inferred← citeshttps://doi.org/10.1177/10943420221107880openalex-snapshot
Enhancing data locality of the conjugate gradient method for high-order matrix-free finite-element implementations
inferred← citeshttps://doi.org/10.23919/splitech52315.2021.9566330openalex-snapshot
Parallelism and Iterative bi-Lanczos Solvers
inferred← citeshttps://doi.org/10.48550/arxiv.2105.06176openalex-snapshot
Efficient executions of Pipelined Conjugate Gradient Method on Heterogeneous Architectures
inferred← citeshttps://doi.org/10.70675/4f3c89b7ze64ez4b7czb25ez6c0589290fc8openalex-snapshot
Contribution to the emergence of new intelligent parallel and distributed methods using a multi-level programming paradigm for extreme computing
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