high performance computing on graphics processing units: hgpu.org

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On-line free-viewpoint video: From single to multiple view rendering

Vincent Nozick, Hideo Saito

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Tags: Computer science, nVidia, nVidia GeForce 7900 GTX, OpenGL, Rendering

December 12, 2010 by hgpu

Map-reduce as a Programming Model for Custom Computing Machines

Jackson H. C. Yeung, C. C. Tsang, K. H. Tsoi, Bill S. H. Kwan, Chris C. C. Cheung, Anthony P. C. Chan, Philip H. W. Leong

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Tags: Computer science, CUDA, FPGA, MapReduce, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GTX, Signal processing

December 12, 2010 by hgpu

A decompression pipeline for accelerating out-of-core volume rendering of time-varying data

Daisuke Nagayasu, Fumihiko Ino, Kenichi Hagihara

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Tags: Cg, Computer science, nVidia, nVidia Quadro FX 4600, OpenGL, Rendering

December 12, 2010 by hgpu

Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Piotr Luszczek, Stanimir Tomov

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Tags: Algorithms, Computer science, Linear Algebra, Mixed precision, Sparse matrix

December 12, 2010 by hgpu

Parallel algorithms for approximation of distance maps on parametric surfaces

Ofir Weber, Yohai S. Devir, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel

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Tags: Algorithms, Cg, Computer science, Numerical Analysis, nVidia, nVidia GeForce 7950 GT

December 12, 2010 by hgpu

A compiler framework for optimization of affine loop nests for gpgpus

Muthu M. Baskaran, Uday Bondhugula, Sriram Krishnamoorthy, J. Ramanujam, Atanas Rountev, P. Sadayappan

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, Optimization

December 12, 2010 by hgpu

Deformable model collision detection using A-buffer

Hanyoung Jang, Junghyun Hany

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Tags: 3D Graphics and Realism, Collision detection, Computer science, DirectX, nVidia, nVidia GeForce 8800 GTS

December 12, 2010 by hgpu

Data parallel execution challenges and runtime performance of agent simulations on GPUs

Kalyan S. Perumalla, Brandon G. Aaby

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Tags: Cg, Computer science, Nearest neighbour, nVidia, nVidia GeForce 8800 GT

December 12, 2010 by hgpu

A Fast Similarity Join Algorithm Using Graphics Processing Units

M. D. Lieberman, J. Sankaranarayanan, H. Samet

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Text mining

December 12, 2010 by hgpu

A map reduce framework for programming graphics processors

Bryan Catanzaro, Narayanan Sundaram, Kurt Keutzer

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Tags: Computer science, CUDA, MapReduce, nVidia, nVidia GeForce 8800 GTX

December 12, 2010 by hgpu

CUDA: Scalable parallel programming for high-performance scientific computing

D. Luebke

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Tags: Computer science, CUDA, High-level Languages, nVidia

December 12, 2010 by hgpu

Deformation modeling using global medial representation structures and evaluation by biset mesh matching

Yanyan Zou, Pengfei Huang, Lixu Gu, Jianghua Wu, Zhennan Yan, Sizhe Lv, Feng Chen, Jiasi Song, Hongshan Zhou, Qi Duan

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Tags: Computer science, CUDA, Finite element method, nVidia, Rendering

December 12, 2010 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

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

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

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

See all packages

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high performance computing on graphics processing units: hgpu.org

On-line free-viewpoint video: From single to multiple view rendering

Map-reduce as a Programming Model for Custom Computing Machines

A decompression pipeline for accelerating out-of-core volume rendering of time-varying data

Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Parallel algorithms for approximation of distance maps on parametric surfaces

A compiler framework for optimization of affine loop nests for gpgpus

Deformable model collision detection using A-buffer

Data parallel execution challenges and runtime performance of agent simulations on GPUs

A Fast Similarity Join Algorithm Using Graphics Processing Units

A map reduce framework for programming graphics processors

CUDA: Scalable parallel programming for high-performance scientific computing

Deformation modeling using global medial representation structures and evaluation by biset mesh matching

Recent source codes

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

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

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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