high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

Linpack evaluation on a supercomputer with heterogeneous accelerators

Toshio Endo, Akira Nukada, Satoshi Matsuoka, Naoya Maruyama

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla S1070

July 17, 2011 by hgpu

Testing Tesla architecture for scientific computing: The performance of matrix-vector product

Pawel Maciol, Krzysztof Banas

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTX, Performance, Tesla C870

July 10, 2011 by hgpu

Numerical Parallel Processing Based on GPU with CUDA Architecture

Chengming Zou, Chunfen Xia, Guanghui Zhao

Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix inversion, nVidia

July 9, 2011 by hgpu

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

Wenjing Ma, Sriram Krishnamoorthy, Oreste Villa, Karol Kowalski

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Tags: Computational chemistry, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Presentation, Tesla C1070, Tesla S1070

July 7, 2011 by hgpu

High Performance Matrix Inversion on a Multi-core Platform with Several GPUs

Pablo Ezzatti, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix inversion, nVidia, Presentation, Tesla C1060

July 5, 2011 by hgpu

Implementing Sparse Matrix-Vector multiplication using CUDA based on a hybrid sparse matrix format

Wei Cao, Lu Yao, Zongzhe Li, Yongxian Wang, Zhenghua Wang

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

June 20, 2011 by hgpu

Auto-tuning Dense Matrix Multiplication for GPGPU with Cache

Xiang Cui, Yifeng Chen, Changyou Zhang, Hong Mei

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

June 19, 2011 by hgpu

CUDA-Based Jacobi’s Iterative Method

Zhihui Zhang, Qinghai Miao, Ying Wang

Tags: Computer science, CUDA, Linear Algebra, nVidia

June 18, 2011 by hgpu

FPGA Based High Performance and Scalable Block LU Decomposition Architecture

Manish Kumar Jaiswal, Nitin Chandrachoodan

Tags: Computer science, FPGA, Linear Algebra, Matrix decomposition

June 14, 2011 by hgpu

A multi-platform linear algebra toolbox for finite element solvers on heterogeneous clusters

V. Heuveline, C. Subramanian, D. Lukarski, J.-P. Weiss

Tags: Finite element method, Heterogeneous systems, Linear Algebra, Mathematics, Partial differential equations, PDEs

June 14, 2011 by hgpu

CUDA Based Fast Implementation of Very Large Matrix Computation

Yinghong Sun, Yuanman Tong

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia

June 10, 2011 by hgpu

Adaptive Optimization for Petascale Heterogeneous CPU/GPU Computing

Canqun Yang, Feng Wang, Yunfei Du, Juan Chen, Jie Liu, Huizhan Yi, Kai Lu

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Tags: ATI, ATI Radeon HD 4870, ATI Stream, Computer science, Heterogeneous systems, Linear Algebra, Optimization, Presentation

June 9, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Linpack evaluation on a supercomputer with heterogeneous accelerators

Testing Tesla architecture for scientific computing: The performance of matrix-vector product

Numerical Parallel Processing Based on GPU with CUDA Architecture

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

High Performance Matrix Inversion on a Multi-core Platform with Several GPUs

Implementing Sparse Matrix-Vector multiplication using CUDA based on a hybrid sparse matrix format

Auto-tuning Dense Matrix Multiplication for GPGPU with Cache

CUDA-Based Jacobi’s Iterative Method

FPGA Based High Performance and Scalable Block LU Decomposition Architecture

A multi-platform linear algebra toolbox for finite element solvers on heterogeneous clusters

CUDA Based Fast Implementation of Very Large Matrix Computation

Adaptive Optimization for Petascale Heterogeneous CPU/GPU Computing

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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