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Cropped Quad-Tree Based Solid Object Colouring with CUDA

Abdullah Cavusoglu, Baha Sen, Caner Ozcan, Salih Gorgunoglu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, nVidia Quadro FX 2000, OpenGL, Rendering

June 30, 2013 by hgpu

Accelerating SELECT WHERE and SELECT JOIN Queries on a GPU

Marcin Pietron, Pawel Russek, Kazimierz Wiatr

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, Tesla M2090

June 30, 2013 by hgpu

HadoopCL: MapReduce on Distributed Heterogeneous Platforms Through Seamless Integration of Hadoop and OpenCL

Max Grossman, Mauricio Breternitz, Vivek Sarkar

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Tags: APU, ATI, Computer science, Heterogeneous systems, Java, MapReduce, nVidia, OpenCL, Tesla M2050

June 30, 2013 by hgpu

Intel Xeon Phi Coprocessor High-Performance Programming

Jim Jeffers, James Jeffers, James Reinders

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Tags: Book, Computer science, Intel, Intel Phi, OpenMP, Package, Review

June 30, 2013 by hgpu

Best Practice Guide – Intel Xeon Phi

Michaela Barth, Mikko Byckling, Nevena Ilieva, Sami Saarinen, Michael Schliephake, Volker Weinberg

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Tags: Computer science, Intel, Intel Phi, OpenMP, Review

June 30, 2013 by hgpu

A model of dynamic compilation for heterogeneous compute platforms

Andrew Kerr

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenCL, PTX, Thesis

June 29, 2013 by hgpu

Adaptation of algorithms for underwater sonar data processing to GPU-based systems

Patricia Sundin

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Tags: Algorithms, CUDA, Earth and Space Sciences, nVidia, nVidia Quadro K5000, OpenCL, Tesla K20, Thesis

June 29, 2013 by hgpu

Hinomiyagura Infrastructure Competiton TDP: Platform of rescue simulation using GPGPU

Toshinori Niwa, Masaru Okaya, Tomoichi Takahashi

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Tags: Computer science, nVidia, OpenCL, Security, Tesla C2075

June 29, 2013 by hgpu

Betatron tune measurement with the LHC damper using a GPU

Frederic Dubouchet

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Tags: CUDA, FFT, Hadronic Colliders, High Energy Physics - Experiment, nVidia, Physics, Thesis

June 29, 2013 by hgpu

Efficient computation of constrained parameterizations on parallel platforms

Theodoros Athanasiadis, Georgios Zioupos, Ioannis Fudos

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Tags: 3D Graphics and Realism, Computer science, nVidia, OpenCL, Package, Tesla C2070

June 29, 2013 by hgpu

An Embedding Method for Interactive Simulation on Dynamic Surfaces

Stefan Auer

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Tags: Computer science, nVidia, nVidia GeForce GTX 480

June 28, 2013 by hgpu

Towards Rapid Prototyping of Parallel and HPC Applications (GPU Focus)

Mohammed S. Al-Mahfoudh

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 440, Thesis

June 28, 2013 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Cropped Quad-Tree Based Solid Object Colouring with CUDA

Accelerating SELECT WHERE and SELECT JOIN Queries on a GPU

HadoopCL: MapReduce on Distributed Heterogeneous Platforms Through Seamless Integration of Hadoop and OpenCL

Intel Xeon Phi Coprocessor High-Performance Programming

Best Practice Guide – Intel Xeon Phi

A model of dynamic compilation for heterogeneous compute platforms

Adaptation of algorithms for underwater sonar data processing to GPU-based systems

Hinomiyagura Infrastructure Competiton TDP: Platform of rescue simulation using GPGPU

Betatron tune measurement with the LHC damper using a GPU

Efficient computation of constrained parameterizations on parallel platforms

An Embedding Method for Interactive Simulation on Dynamic Surfaces

Towards Rapid Prototyping of Parallel and HPC Applications (GPU Focus)

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

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

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