high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

The BiConjugate gradient method on GPUs

G. Ortega, E. M. Garzon, F. Vazquez, I. Garcia

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 15, 2012 by hgpu

Batch Records Insertion into Multidimensional Linear Dynamic Hashing Table on GPU

Yong Liu, Jianqing Xi, Zhengwen Lai, Dongping Huang

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 550 Ti

May 15, 2012 by hgpu

An Automatic Speech Recognition Application Framework for Highly Parallel Implementations on the GPU

Jike Chong, Ekaterina Gonina, Dorothea Kolossa, Steffen Zeiler, Kurt Keutzer

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Tags: Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 480, Programming techniques, Speech recognition

May 15, 2012 by hgpu

Real-time Traffic Sign Recognition with Map Fusion on Multicore/Many-core Architectures

Kerem Par, Oguz Tosun

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 580

May 15, 2012 by hgpu

Mapping a Data-Flow Programming Model onto Heterogeneous Platforms

Alina Sbirlea, Yi Zou, Zoran Budimlic, Jason Cong, Vivek Sarkar

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Tags: Algorithms, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Programming techniques, Tesla C1060

May 14, 2012 by hgpu

Scalable Distributed Fast Multipole Methods

Qi Hu, Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla C2050

May 12, 2012 by hgpu

Parallel Cryptanalysis

Ruben Falko Niederhagen

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 295, PTX, Security, Thesis

May 12, 2012 by hgpu

Characterization and Transformation of Unstructured Control Flow in Bulk Synchronous GPU Applications

Haicheng Wu, Gregory Diamos, Jin Wang, Si Li, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, nVidia, OpenCL

May 12, 2012 by hgpu

Enhancing GPU Parallelism in Nature-Inspired Algorithms

Jose M. Cecilia, Andy Nisbet, Martyn Amos, Jose M. Garcia, Manuel Ujaldon

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Tags: Algorithms, Computational modelling, Computer science, CUDA, Data parallelism, nVidia, Optimization, P systems, Tesla C1060, Tesla C2050

May 12, 2012 by hgpu

Efficient Parallelization of Natural Language Applications using GPUs

Chao-Yue Lai

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Thesis

May 11, 2012 by hgpu

Data Regression with Normal Equation on GPU using CUDA

Vaibhav Mohan, Mayank Gupta

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Tags: Algorithms, Computer science, CUDA, nVidia

May 11, 2012 by hgpu

Large scale parallel state space search utilizing graphics processing units and solid state disks

Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Probabilistic model checking, Search strategies, Thesis

May 11, 2012 by hgpu

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

The BiConjugate gradient method on GPUs

Batch Records Insertion into Multidimensional Linear Dynamic Hashing Table on GPU

An Automatic Speech Recognition Application Framework for Highly Parallel Implementations on the GPU

Real-time Traffic Sign Recognition with Map Fusion on Multicore/Many-core Architectures

Mapping a Data-Flow Programming Model onto Heterogeneous Platforms

Scalable Distributed Fast Multipole Methods

Parallel Cryptanalysis

Characterization and Transformation of Unstructured Control Flow in Bulk Synchronous GPU Applications

Enhancing GPU Parallelism in Nature-Inspired Algorithms

Efficient Parallelization of Natural Language Applications using GPUs

Data Regression with Normal Equation on GPU using CUDA

Large scale parallel state space search utilizing graphics processing units and solid state disks

Recent source codes

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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