high performance computing on graphics processing units: hgpu.org

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Point to Line Mappings and Other Line Parameterizations not only for Hough Transform

Jiri Havel

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 280, OpenGL, Pattern recognition

October 15, 2013 by hgpu

Massively Parallel Lossless Compression of Medical Images Using Least-Squares Prediction and Arithmetic Coding

Andreas Weinlich, Johannes Rehm, Peter Amon, Andreas Hutter, Andre Kaup

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Tags: Compression, CUDA, Image processing, Medicine, nVidia, nVidia GeForce GTX 480

October 15, 2013 by hgpu

High-Performance GPGPU Programming with OCaml

Mathias Bourgoin, Emmanuel Chailloux, Jean-Luc Lamotte

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Tags: ATI, ATI Radeon HD 6950, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 680, OpenCL, Tesla C2070

October 15, 2013 by hgpu

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

Stefan Kiel, Ekaterina Auer, Andreas Rauh

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 580, ODEs, Ordinary differential equations

October 15, 2013 by hgpu

Power Control for GPU Clusters in processing large-scale streams

Qingkui Chen, Haifeng Wang, Bocheng Liu

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Tags: Computer science, CUDA, Energy-efficient computing, GPU cluster, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480

October 13, 2013 by hgpu

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Jonathan Passerat-Palmbach

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Tags: Algorithms, Computer science, CUDA, Java, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Pseudo-random number generators, Software Engineering, Stochastic simulation, Tesla C2050, Tesla C2075, Tesla K20, Thesis

October 13, 2013 by hgpu

Simulating Active Membrane Systems Using GPUs

Miguel A. Martinez-del-Amor, Ignacio Perez-Hurtado, Mario J. Perez-Jimenez, Jose M. Cecilia, Gines D. Guerrero, Jose M. Garcia

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Tags: Computer science, CUDA, Membrane computing, nVidia, Tesla C1060

October 13, 2013 by hgpu

Characterizing the Challenges and Evaluating the Efficacy of a CUDA-to-OpenCL Translator

Mark Gardner, Paul Sathre, Wu-chun Feng, Gabriel Martinez

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

October 13, 2013 by hgpu

High performance sequence mining using pairwise statistical significance

Yuhong Zhang, Feng Chen

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Source codes

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

October 12, 2013 by hgpu

Regional Heritability Advanced Complex Trait Analysis for GPU and Traditional Parallel Architectures

L. Cebamanos, A. Gray, I. Stewart, A. Tenesa

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla K20

October 12, 2013 by hgpu

Coupling a Generalized DEM and an SPH Models Under a Heterogeneous Massively Parallel Framework

Ricardo Canelas, Jose M. Dominguez, Rui M. L. Ferreira

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, MPI, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 680

October 12, 2013 by hgpu

Automatic run-time mapping of polyhedral computations to heterogeneous devices with memory-size restrictions

Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, nVidia GeForce GTX 680

October 12, 2013 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

Point to Line Mappings and Other Line Parameterizations not only for Hough Transform

Massively Parallel Lossless Compression of Medical Images Using Least-Squares Prediction and Arithmetic Coding

High-Performance GPGPU Programming with OCaml

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

Power Control for GPU Clusters in processing large-scale streams

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Simulating Active Membrane Systems Using GPUs

Characterizing the Challenges and Evaluating the Efficacy of a CUDA-to-OpenCL Translator

High performance sequence mining using pairwise statistical significance

Regional Heritability Advanced Complex Trait Analysis for GPU and Traditional Parallel Architectures

Coupling a Generalized DEM and an SPH Models Under a Heterogeneous Massively Parallel Framework

Automatic run-time mapping of polyhedral computations to heterogeneous devices with memory-size restrictions

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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