high performance computing on graphics processing units: hgpu.org

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Real-time Spatiotemporal Stereo Matching Using the Dual-Cross-Bilateral Grid

Christian Richardt, Douglas Orr, Ian Davies, Antonio Criminisi and Neil A. Dodgson

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia Quadro FX 5800, Package

February 7, 2011 by hgpu

Financial modeling on the cell broadband engine

Virat Agarwal, Lurng-Kuo Liu, David A. Bader

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Tags: Cell processor, CUDA, Finance, Monte Carlo simulation, nVidia, nVidia GeForce 8800, RapidMind

February 6, 2011 by hgpu

Evaluating multi-core platforms for HPC data-intensive kernels

Alexander S. van Amesfoort, Ana Lucia Varbanescu, Henk J. Sips, Rob V. van Nieuwpoort

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Tags: Algorithms, Cell processor, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Programming techniques, Tesla C1060

February 6, 2011 by hgpu

Focused Volumetric Visual Hull with Color Extraction

Daniel Knoblauch, Falko Kuester

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce 8800 GTX

February 6, 2011 by hgpu

Regular Expression Matching on Graphics Hardware for Intrusion Detection

Giorgos Vasiliadis, Michalis Polychronakis, Spiros Antonatos, Evangelos P. Markatos and Sotiris Ioannidis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, Security, String matching

February 5, 2011 by hgpu

Software Pipelined Execution of Stream Programs on GPUs

Abhishek Udupa, R. Govindarajan, Matthew J. Thazhuthaveeti

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTS, Package

February 5, 2011 by hgpu

NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs

Andreas Fidjeland, Etienne B. Roesch, Murray P. Shanahan, Wayne Luk

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, Package, Tesla C1060

February 5, 2011 by hgpu

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

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

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

February 5, 2011 by hgpu

Real-Time Face Pose Estimation from Single Range Images

Michael D. Breitenstein, Daniel Kuettel, Thibaut Weise, Luc van Gool, and Hanspeter Pfister

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX

February 5, 2011 by hgpu

QR decomposition on GPUs

Andrew Kerr, Dan Campbell, Mark Richards

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

February 5, 2011 by hgpu

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

Grand Roman Joldes, Adam Wittek, Mathieu Couton, Simon K. Warfield and Karol Miller

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Tags: CUDA, Finite element method, Image processing, Image registration, Medicine, MRI, nVidia

February 5, 2011 by hgpu

Accelerating total variation regularization for matrix-valued images on GPUs

Maryam Moazeni, Alex A. T. Bui, Majid Sarrafzadeh

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia Quadro FX 5600

February 4, 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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

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high performance computing on graphics processing units: hgpu.org

Real-time Spatiotemporal Stereo Matching Using the Dual-Cross-Bilateral Grid

Financial modeling on the cell broadband engine

Evaluating multi-core platforms for HPC data-intensive kernels

Focused Volumetric Visual Hull with Color Extraction

Regular Expression Matching on Graphics Hardware for Intrusion Detection

Software Pipelined Execution of Stream Programs on GPUs

NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs

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

Real-Time Face Pose Estimation from Single Range Images

QR decomposition on GPUs

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

Accelerating total variation regularization for matrix-valued images on GPUs

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)

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

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