high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

A Parallel Jacobi-Type Lattice Basis Reduction Algorithm

Filip Jeremic, Sanzheng Qiao

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 660

May 26, 2014 by hgpu

A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU

Tingxing Dong, Veselin Dobrev, Tzanio Kolev, Robert Rieben, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, FEM, Finite element method, Linear Algebra, nVidia, Tesla K20

May 20, 2014 by hgpu

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680

May 14, 2014 by hgpu

Analysis of SuperLU Solvers on Intel MIC Architecture

Ahmet Duran, M. Serdar Celebi, Bora Akaydin, Mehmet Tuncel, Figen Oztoprak

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Tags: Computer science, Intel Xeon Phi, Linear Algebra, Sparse matrix

May 2, 2014 by hgpu

Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Hartwig Anzt, Dimitar Lukarski, Stanimire Tomov, Jack Dongarra

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Tesla K40

April 27, 2014 by hgpu

Integrating multi-threading and accelerators into DUNE-ISTL

Steffen Muthing, Dirk Ribbrock, Dominik Goddeke

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Partial differential equations, PDEs, Tesla C2070

April 25, 2014 by hgpu

Galerkin-based multi-scale time integration for nonlinear structural dynamics

Matthias Bartelt, Michael Gross

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Tags: CUDA, Differential equations, Linear Algebra, Mathematics, Numerical simulation, nVidia, ODEs, Ordinary differential equations, Partial differential equations, PDEs, Tesla C2075

April 24, 2014 by hgpu

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Luka Stanisic, Samuel Thibault, Arnaud Legrand, Brice Videau, Jean-Francois Mehaut

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Performance, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075

April 9, 2014 by hgpu

Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

Hartwig Anzt, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Sorting, Sparse matrix, Tesla K40

April 7, 2014 by hgpu

Optimizing Krylov Subspace Solvers on Graphics Processing Units

Hartwig Anzt, Stanimire Tomov, Piotr Luszczek, Ichitaro Yamazaki, Jack Dongarra, William Sawyer

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla K20

April 6, 2014 by hgpu

Parallel Support Vector Machines in Practice

Stephen Tyree, Jacob R. Gardner, Kilian Q. Weinberger, Kunal Agrawal, John Tran

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Source codes

Tags: Algorithms, Benchmarking, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, Package, Tesla C2075

April 6, 2014 by hgpu

Experiments with Massively Parallel Matrix Multiplication

T. W. O’Neil

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Tags: Algorithms, CUDA, Linear Algebra, Mathematics, nVidia, nVidia Tesla C2070

April 3, 2014 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

A Parallel Jacobi-Type Lattice Basis Reduction Algorithm

A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Analysis of SuperLU Solvers on Intel MIC Architecture

Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Integrating multi-threading and accelerators into DUNE-ISTL

Galerkin-based multi-scale time integration for nonlinear structural dynamics

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

Optimizing Krylov Subspace Solvers on Graphics Processing Units

Parallel Support Vector Machines in Practice

Experiments with Massively Parallel Matrix Multiplication

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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