high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

Scaling LAPACK panel operations using parallel cache assignment

Anthony M. Castaldo, R. Clint Whaley

View

Download (PDF)

Tags: Algorithms, Computer science, Factorization, Linear Algebra, Mathematical Software, Performance

February 10, 2011 by hgpu

Model-driven autotuning of sparse matrix-vector multiply on GPUs

Jee W. Choi, Amik Singh, Richard W. Vuduc

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla C1060, Tesla C870, Tesla T10P

February 5, 2011 by hgpu

QR decomposition on GPUs

Andrew Kerr, Dan Campbell, Mark Richards

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280

February 5, 2011 by hgpu

Constraint Fluids on GPU

Martin Nilsson

View

Download (PDF)

Tags: Algorithms, Collision detection, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Thesis

February 1, 2011 by hgpu

Efficient Sparse Matrix-Vector Multiplication on CUDA

Nathan Bell and Michael Garland

View

Download (PDF)

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

An Improved Magma Gemm For Fermi Graphics Processing Units

Rajib Nath, Stanimire Tomov, Jack Dongarra

View

Download (PDF)

Source codes

Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Package, Tesla C2050

January 23, 2011 by hgpu

Fast development of dense linear algebra codes on graphics processors

M. Jesus Zafont, Alberto F. Martin, Francisco Igual, Enrique S. Quintana-Orti

View

Download (PDF)

Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

January 20, 2011 by hgpu

Solving dense linear systems on platforms with multiple hardware accelerators

Enrique S. Quintana-Orti, Francisco D. Igual, Enrique S. Quintana-Orti, Robert A. van de Geijn

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, GPU cluster, Linear Algebra, nVidia, Package, Task scheduling, Tesla S870

January 17, 2011 by hgpu

Accelerating linpack with CUDA on heterogenous clusters

Massimiliano Fatica

Tags: Computer science, CUDA, GPU cluster, Linear Algebra, nVidia

January 11, 2011 by hgpu

Evaluation and tuning of the Level 3 CUBLAS for graphics processors

S. Barrachina, M. Castillo, F. D. Igual, R. Mayo, E. S. Quintana-Orti

View

Download (PDF)

Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

January 9, 2011 by hgpu

A complete modular resultant algorithm targeted for realization on graphics hardware

Pavel Emeliyanenko

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 5, 2011 by hgpu

Modular Resultant Algorithm for Graphics Processors

Pavel Emeliyanenko

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 5, 2011 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

* * *

high performance computing on graphics processing units: hgpu.org

Scaling LAPACK panel operations using parallel cache assignment

Model-driven autotuning of sparse matrix-vector multiply on GPUs

QR decomposition on GPUs

Constraint Fluids on GPU

Efficient Sparse Matrix-Vector Multiplication on CUDA

An Improved Magma Gemm For Fermi Graphics Processing Units

Fast development of dense linear algebra codes on graphics processors

Solving dense linear systems on platforms with multiple hardware accelerators

Accelerating linpack with CUDA on heterogenous clusters

Evaluation and tuning of the Level 3 CUBLAS for graphics processors

A complete modular resultant algorithm targeted for realization on graphics hardware

Modular Resultant Algorithm for Graphics Processors

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

Most viewed papers (last 30 days)