high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Parallel face Detection and Recognition on GPU

Shivashankar J. Bhutekar, Arati K. Manjaramkar

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 770

April 9, 2014 by hgpu

Real-time and Realistic Simulation of Large-scale Deep Ocean Wave Foams Based on GPU

Lihui Zhang, Cuiying Guo, Yong Tang, Mengya Lv, Ying Li, Jing Zhao

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Tags: 3D Graphics and Realism, Computer science, CUDA, FFT, Fluid simulation, nVidia, nVidia GeForce GT 630

April 9, 2014 by hgpu

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Luka Stanisic, Samuel Thibault, Arnaud Legrand, Brice Videau, Jean-Francois Mehaut

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Performance, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075

April 9, 2014 by hgpu

Task-based FMM for heterogeneous architectures

Emmanuel Agullo, Berenger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, Toru Takahashi

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Tags: Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla M2070, Tesla M2090

April 9, 2014 by hgpu

A two-level task scheduler on Multiple DSP system for OpenCL

Li Tian, Cai Meng, Fugen Zhou

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Tags: Computer science, DSP, nVidia, OpenCL, Task scheduling

April 9, 2014 by hgpu

Bayesian Sparse Unsupervised Learning for Probit Models of Binary Data

Ari Pakman, Ben Shababo, Liam Paninski

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Tags: Bayesian, Computer science, CUDA, nVidia, Python

April 9, 2014 by hgpu

Reducing the Disk IO Bandwidth Bottleneck through Fast Floating Point Compression using Accelerators

Ajith Padyana, Devi Sudheer, Pallav Kumar Baruah, Ashok Srinivasan

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Tags: Algorithms, Cell processor, Compression, Computer science, CUDA, nVidia, Tesla M2050

April 9, 2014 by hgpu

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Zheng Xia

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Tags: Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Review

April 9, 2014 by hgpu

Exploring the power of GPU’s for training Deep Belief Networks

Vivek Kulkarni

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 570

April 9, 2014 by hgpu

A New Non-Blocking Approach on GPU Dynamical Memory Management

Yu-Shiang Lin, Chun-Yuan Lin, Jon-Yu Lee

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Tags: Computer science, CUDA, Memory model, nVidia, Performance, Tesla K20

April 7, 2014 by hgpu

State of the Art Report on Real-time Rendering with Hardware Tessellation

Henry Schafer, Matthias Niessner, Benjamin Keinert, Marc Stamminger, Charles Loop

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Tags: 3D Graphics and Realism, Computer science, DirectX, Interactive application, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 780, Rendering, Tessellation

April 7, 2014 by hgpu

Quantifying the Energy Efficiency of Object Recognition and Optical Flow

Michael Anderson, Forrest Iandola, Kurt Keutzer

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Tags: Algorithms, ATI, ATI Radeon HD 7990, Computer science, Neural networks, OpenCL, Optical flow

April 7, 2014 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

Parallel face Detection and Recognition on GPU

Real-time and Realistic Simulation of Large-scale Deep Ocean Wave Foams Based on GPU

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Task-based FMM for heterogeneous architectures

A two-level task scheduler on Multiple DSP system for OpenCL

Bayesian Sparse Unsupervised Learning for Probit Models of Binary Data

Reducing the Disk IO Bandwidth Bottleneck through Fast Floating Point Compression using Accelerators

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Exploring the power of GPU’s for training Deep Belief Networks

A New Non-Blocking Approach on GPU Dynamical Memory Management

State of the Art Report on Real-time Rendering with Hardware Tessellation

Quantifying the Energy Efficiency of Object Recognition and Optical Flow

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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