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Effective GPU Strategies for LU Decomposition

Dinesh Bandara, Nalin Ranasinghe

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Tags: Algorithms, Computer science, CUDA, Matrix decomposition, nVidia, Tesla C1060

December 2, 2011 by hgpu

An error correction solver for linear systems: Evaluation of mixed precision implementations

Hartwig Anzt, Vincent Heuveline, Bjorn Rocker

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Tags: Benchmarking, Computer science, CUDA, Mixed precision, nVidia, Tesla S1070

December 2, 2011 by hgpu

Auto-optimization of a Feature Selection Algorithm

Didem Unat, Han Suk Kim, Jurgen P. Schulze, Scott B. Baden

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Optimization, Rendering, Tesla C1060, Visualization

December 2, 2011 by hgpu

Evaluation of Fermi Features for Data Mining Algorithms

Sinduja Muralidharan

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, Nearest neighbour, nVidia, Tesla C1060, Tesla C2050, Thesis

December 2, 2011 by hgpu

A programming language interface to describe transformations and code generation

Gabe Rudy, Malik Murtaza Khan, Mary Hall, Chun Chen, Jacqueline Chame

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Tags: Algorithms, Code generation, Computer science, CUBLAS, CUDA, MPI, nVidia, nVidia GeForce GTX 280, Tesla C2050

December 1, 2011 by hgpu

GPU Acceleration of Solving Parabolic Partial Differential Equations Using Difference Equations

David L. Foster

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 480, Optimization, Partial differential equations, PDEs, Tesla C1060

December 1, 2011 by hgpu

Scalable Data Clustering using GPU Clusters

Andrew Pangborn, Gregor von Laszewski, James Cavenaugh, Muhammad Shaaban, Roy Melton

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Tags: Algorithms, Cloud, Clustering, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GTX 260, OpenMP, Tesla C1060

December 1, 2011 by hgpu

Architecture-Aware Algorithms and Software for Peta and Exascale Computing

Jack J. Dongarra

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Tags: Algorithms, Computer science, Mixed precision, MPI, Review

November 30, 2011 by hgpu

Using CUDA for Exhaustive Password Recovery

Tore Kasper Frederiksen

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9400 M, nVidia GeForce GTX 480, Package, Security

November 30, 2011 by hgpu

Optimization of the Particle-based Volume Rendering for GPUs with Hiding Data Transfer Latency

Kyoko Nakao, Erika Matsui, Naoko Yoshii, Masami Takata, Kazuki Joe

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8400 GS, Optimization, Rendering, Tesla C1060

November 30, 2011 by hgpu

Performance and numerical accuracy evaluation of heterogeneous multicore systems for Krylov orthogonal basis computation

Jerome Dubois, Christophe Calvin, Serge Petiton

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Tags: Cell processor, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060

November 30, 2011 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

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high performance computing on graphics processing units: hgpu.org

Effective GPU Strategies for LU Decomposition

An error correction solver for linear systems: Evaluation of mixed precision implementations

Auto-optimization of a Feature Selection Algorithm

Evaluation of Fermi Features for Data Mining Algorithms

A programming language interface to describe transformations and code generation

GPU Acceleration of Solving Parabolic Partial Differential Equations Using Difference Equations

Architecture-Aware Algorithms and Software for Peta and Exascale Computing

Using CUDA for Exhaustive Password Recovery

Optimization of the Particle-based Volume Rendering for GPUs with Hiding Data Transfer Latency

Performance and numerical accuracy evaluation of heterogeneous multicore systems for Krylov orthogonal basis computation

Applications Performance on GPGPUs with the Fermi Architecture

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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