high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

GPU and CPU Cooperative Accelerated Road Detection

Peng Xiong, Cheng Xu, Zheng Tian, Tao Li

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Tags: Computer science, Computer vision, Neural networks, OpenCV

December 3, 2013 by hgpu

SESH framework: A Space Exploration Framework for GPU Application and Hardware Codesign

Joo Hwan Lee, Jiayuan Meng, Hyesoon Kim

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GTX 580, Performance

December 3, 2013 by hgpu

Real-time High Resolution Fusion of Depth Maps on GPU

Dmitry Trifonov

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Tags: Algorithms, Computer science, Computer vision, Graphics, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 560 Ti, OpenCL

December 3, 2013 by hgpu

GenBase: A Complex Analytics Genomics Benchmark

Rebecca Taft, Manasi Vartak, Nadathur Rajagopalan Satish, Narayanan Sundaram, Samuel Madden, Michael Stonebraker

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Tags: Benchmarking, Computer science, Intel Phi, Intel Xeon Phi

November 30, 2013 by hgpu

Fractal Based Method on Hardware Acceleration for Natural Environments

Divya Udayan J, HyungSeok Kim, Jun Lee, Jee-In Kim

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 650, Rendering

November 30, 2013 by hgpu

Digitize Your Body and Action in 3-D at Over 10 FPS: Real Time Dense Voxel Reconstruction and Marker-less Motion Tracking via GPU Acceleration

Jian Song, Yatao Bian, Junchi Yan, Xu Zhao, Yuncai Liu

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Tags: Algorithms, ATI, ATI Radeon HD 6870, Computer science, Computer vision, Graphics, OpenCL, OpenCV

November 30, 2013 by hgpu

GPU Accelerated Parallel Occupancy Voxel Based ICP for Position Tracking

Adrian Ratter, Claude Sammut

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 570, OpenCL

November 30, 2013 by hgpu

Benchmarking Parallel Performance on Many-Core Processors

Bryant C. Lam, Ajay Barboza, Ravi Agrawal, Alan D. George, Herman Lam

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Phi, Intel Xeon Phi, Performance

November 29, 2013 by hgpu

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Kamil Rocki, Martin Burtscher, Reiji Suda

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Programming techniques

November 28, 2013 by hgpu

The Use of Automated Search in Deriving Software Testing Strategies

Simon Marcus Poulding

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, Tesla C1060, Thesis

November 28, 2013 by hgpu

American Basket Option Pricing on a multi GPU Cluster

Michael Benguigui, Francoise Baude

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Tags: Algorithms, Computer science, GPU cluster, nVidia, OpenCL, Tesla M2050, Tesla S1070

November 28, 2013 by hgpu

Hybrid Programming using OpenSHMEM and OpenACC

Matthew Baker, Swaroop Pophale, Jean-Charles Vasnier, Haoqiang Jin, Oscar Hernandez

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Tags: Computer science, CUDA, MPI, nVidia, OpenACC, Performance, Tesla K20

November 28, 2013 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

GPU and CPU Cooperative Accelerated Road Detection

SESH framework: A Space Exploration Framework for GPU Application and Hardware Codesign

Real-time High Resolution Fusion of Depth Maps on GPU

GenBase: A Complex Analytics Genomics Benchmark

Fractal Based Method on Hardware Acceleration for Natural Environments

Digitize Your Body and Action in 3-D at Over 10 FPS: Real Time Dense Voxel Reconstruction and Marker-less Motion Tracking via GPU Acceleration

GPU Accelerated Parallel Occupancy Voxel Based ICP for Position Tracking

Benchmarking Parallel Performance on Many-Core Processors

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

The Use of Automated Search in Deriving Software Testing Strategies

American Basket Option Pricing on a multi GPU Cluster

Hybrid Programming using OpenSHMEM and OpenACC

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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