high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Automatic Resource-Constrained Static Task Parallelization

Dounia Khaldi

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Tags: Algorithms, Code generation, Computer science, MPI, OpenCL, Task scheduling, Thesis

January 28, 2014 by hgpu

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications

Bo Fang, Karthik Pattabiraman, Matei Ripeanu, Sudhanva Gurumurthi

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Tags: Computer science, CUDA, GPGPU-sim, nVidia

January 28, 2014 by hgpu

Performance-Correctness Challenges in Emerging Heterogeneous Multicore Processors

Vineeth Thamarassery Mekkat

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce 8600 GTS, Thesis

January 28, 2014 by hgpu

Autotuning Programs with Algorithmic Choice

Jason Ansel

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Tags: Algorithms, ATI, ATI Radeon HD 6630 M, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2070, Thesis

January 28, 2014 by hgpu

gem5-gpu: A Heterogeneous CPU-GPU Simulator

Jason Power, Joel Hestness, Marc S. Orr, Mark D. Hill, David A. Wood

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Tags: Computer science, CUDA, GPGPU-sim, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

January 26, 2014 by hgpu

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Marcel Koster, Roland Leissa, and Sebastian Hack, Richard Membarth, Philipp Slusallek

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

January 26, 2014 by hgpu

Computing Best Possible Pseudo-Solutions to Interval Linear Systems of Equations

Anatoly V. Panyukov, Valentin A. Golodov

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Tags: Computer science, CUDA, Linear Algebra, MPI, nVidia, nVidia GeForce GTX 460

January 26, 2014 by hgpu

Low-latency Image Recognition with GPU-accelerated Convolutional Networks for Web-based Services

Fu Jie Huang

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Tags: Cloud, CUDA, Image processing, Image recognition, nVidia, nVidia GeForce GTX 560 Ti, Thesis

January 26, 2014 by hgpu

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Naoya Maruyama, Takayuki Aoki

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla K20, Tesla M2075

January 26, 2014 by hgpu

Hybrid strategy for stencil computations on the APU

Pacome Eberhart, Issam Said, Pierre Fortin

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Tags: AMD, APU, Computer science, Numerical Analysis, OpenCL, Partial differential equations

January 26, 2014 by hgpu

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

Jinwei Wang, Xirong Ma, Yuanping Zhu, Jizhou Sun

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

January 26, 2014 by hgpu

GPU acceleration of Newton’s method for large systems of polynomial equations in double double and quad double arithmetic

Jan Verschelde, Xiangcheng Yu

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Tags: Algorithms, CUDA, Extended precision, Linear Algebra, Mathematics, nVidia, Tesla C2050, Tesla K20

January 26, 2014 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

Programming

Automatic Resource-Constrained Static Task Parallelization

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications

Performance-Correctness Challenges in Emerging Heterogeneous Multicore Processors

Autotuning Programs with Algorithmic Choice

gem5-gpu: A Heterogeneous CPU-GPU Simulator

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Computing Best Possible Pseudo-Solutions to Interval Linear Systems of Equations

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Hybrid strategy for stencil computations on the APU

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

GPU acceleration of Newton’s method for large systems of polynomial equations in double double and quad double arithmetic

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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