high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

Parallel GPU Implementation of Iterative PCA Algorithms

M. Andrecut

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Tags: Algorithms, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

November 13, 2010 by hgpu

Accelerating Scientific Computations with Mixed Precision Algorithms

Marc Baboulin, Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Julie Langou, Julien Langou, Piotr Luszczek, Stanimire Tomov

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Tags: Algorithms, Cell processor, Computer science, FPGA, Linear Algebra, Mathematical Software, Mixed precision

November 9, 2010 by hgpu

Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems

Stanimire Tomov, Jack Dongarra, Marc Baboulin

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

November 8, 2010 by hgpu

Faster matrix-vector multiplication on GeForce 8800GTX

N. Fujimoto

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

November 5, 2010 by hgpu

Benchmarking GPUs to tune dense linear algebra

Vasily Volkov, James W. Demmel

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280

November 4, 2010 by hgpu

Solving Dense Linear Systems on Graphics Processors

Sergio Barrachina, Maribel Castillo, Francisco D. Igual, Rafael Mayo, Enrique S. Quintana Ort'?

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

November 4, 2010 by hgpu

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Nathan Bell, Michael Garland

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Source codes

Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Package, Sparse matrix

November 4, 2010 by hgpu

Algorithmic performance studies on graphics processing units

O. Schenk, M. Christen, H. Burkhart

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Tags: Computer science, Linear Algebra, Matrix decomposition, Nonlinear optimization, nVidia, nVidia GeForce 8800 GTX, Sparse direct solvers

November 2, 2010 by hgpu

Linear algebra operators for GPU implementation of numerical algorithms

Jens Krüger, Rüdiger Westermann

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Tags: 3D Graphics and Realism, ATI, ATI Radeon 9800, Computer science, Finite difference, Fluid simulation, Linear Algebra, Navier-Stokes equations, NSEs, OpenGL, Raytracing, Rendering, Simulation support systems

November 2, 2010 by hgpu

Improving Performance of Matrix Multiplication and FFT on GPU

Xiang Cui, Yifeng Chen, Hong Mei

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

November 2, 2010 by hgpu

Parallel Processing of Matrix Multiplication in a CPU and GPU Heterogeneous Environment

Satoshi Ohshima, Kenji Kise, Takahiro Katagiri, Toshitsugu Yuba

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Tags: Algorithms, Computer science, Linear Algebra, nVidia GeForce 6600 GT, nVidia GeForce 7800 GTX

October 29, 2010 by hgpu

Cache and bandwidth aware matrix multiplication on the GPU

J. Hall, N. Carr, J. Hart

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Tags: Algorithms, Computer science, Linear Algebra, Performance

October 27, 2010 by hgpu

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Automating Heterogeneous Parallelism in Numerical Differential Equations

Dat3M: Memory Model Aware Verification

Towards Unified Analysis of GPU Consistency

NVIDIA Federated Learning Application Runtime Environment

Supercharging Federated Learning with Flower and NVIDIA FLARE

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

General-purpose Polyhedral Compilers

A Survey of General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

See all packages

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high performance computing on graphics processing units: hgpu.org

Parallel GPU Implementation of Iterative PCA Algorithms

Accelerating Scientific Computations with Mixed Precision Algorithms

Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems

Faster matrix-vector multiplication on GeForce 8800GTX

Benchmarking GPUs to tune dense linear algebra

Solving Dense Linear Systems on Graphics Processors

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Algorithmic performance studies on graphics processing units

Linear algebra operators for GPU implementation of numerical algorithms

Improving Performance of Matrix Multiplication and FFT on GPU

Parallel Processing of Matrix Multiplication in a CPU and GPU Heterogeneous Environment

Cache and bandwidth aware matrix multiplication on the GPU

Recent source codes

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Dat3M: Memory Model Aware Verification

NVIDIA Federated Learning Application Runtime Environment

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

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