high performance computing on graphics processing units: hgpu.org

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Review of Memory/Cache Management Technologies used on Heterogeneous Computing Systems

Mustafa Ali, Tarik Ozkul

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Tags: Computer science, Heterogeneous systems, Memory, Review

May 23, 2014 by hgpu

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Christoph Kessler, Usman Dastgeer, Lu Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Review, Tesla C2050

May 15, 2014 by hgpu

K-Means on GPU: A Review

Vidya Dhamdhere, Rahul G. Ghudji

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, Review

May 13, 2014 by hgpu

Atmospheric Chemistry

Istvan Lagzi, Robert Meszaros, Gyorgyi Gelybo, Adam Leelossy

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Tags: Book, Chemistry, CUDA, Earth and Space Sciences, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, Review

April 30, 2014 by hgpu

Analysis and Review of Sorting Algorithms

Gaurav Kocher, Nikita Agrawa

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Tags: Algorithms, Computer science, OpenCL, Review, Sorting

April 12, 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

Data Mining Techniques in Parallel and Distributed Environment – A Comprehensive Survey

S. Masih, S. Tanwani

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Tags: CUDA, Data mining, Databases, Review

March 31, 2014 by hgpu

Literature review: Build and Travel KD-Tree with CUDA

M. Zhou

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Tags: CUDA, Graphics, KD-tree, Raytracing, Review

March 29, 2014 by hgpu

GPU-based high-performance computing for radiation therapy

Xun Jia, Peter Ziegenhein, Steve B Jiang

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Tags: CUDA, Medicine, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 570, nVidia GeForce GTX 580, nVidia GeForce GTX 590, Physics, Radiotherapy, Review, Tesla C1060, Tesla C2050, Tesla C2070

February 9, 2014 by hgpu

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Ani Anciaux-Sedrakian, Peter Gottschling, Jean-Marc Gratien, Thomas Guignon

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Review, Tesla M2070, Tesla M2090

February 1, 2014 by hgpu

Clustering on GPU – A Brief Survey

V.Saveetha, S.Sophia, V.Anusha Sowbarnika

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Review

September 27, 2013 by hgpu

Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

Kyle E Niemeyer, Chih-Jen Sung

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Tags: Algorithms, Computational Physics, CUDA, Fluid dynamics, Lattice Boltzmann model, Navier-Stokes equations, NSEs, nVidia, OpenACC, Package, Review, Tesla C2075

September 13, 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

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high performance computing on graphics processing units: hgpu.org

Review of Memory/Cache Management Technologies used on Heterogeneous Computing Systems

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

K-Means on GPU: A Review

Atmospheric Chemistry

Analysis and Review of Sorting Algorithms

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

Data Mining Techniques in Parallel and Distributed Environment – A Comprehensive Survey

Literature review: Build and Travel KD-Tree with CUDA

GPU-based high-performance computing for radiation therapy

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Clustering on GPU – A Brief Survey

Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

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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