high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Multilevel Tile Load Map on Massive Terrain Visualization

Junlan Nie, Dongliang Guo, Yanfen Wang, Lingfu Kong, Yong Tang

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Tags: Algorithms, Computer science, GLSL, Image processing, nVidia, nVidia GeForce GT 240 M, OpenGL, Optimization, Rendering, Visualization

December 28, 2011 by hgpu

GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

Marco Maggioni, Marco Domenico Santambrogio, Jie Liang

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Tags: Algorithms, Chemistry, CUDA, Databases, nVidia, nVidia GeForce 9400 M, nVidia GeForce GTX 460, Optimization

December 27, 2011 by hgpu

Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

Mikolaj Mackowiak, Krzysztof Kurowski, Aleksandr Igumenov

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Source codes

Tags: Algorithms, Computer science, CUDA, Distributed computing, Hybrid computing, MPI, nVidia, Optimization, Package

December 27, 2011 by hgpu

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Qi Li

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Optimization, Sorting, Tesla C1060, Tesla C2050, Tesla C2070, Thesis

December 26, 2011 by hgpu

Image processing algorithm optimization with CUDA for Pure Data

Rudi Giot, Abilio Rodrigues e Sousa

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Tags: Algorithm optimization, Algorithms, CUDA, Image processing, nVidia, Optimization

December 24, 2011 by hgpu

GPU Pathfinding Optimization

Adonis Silva, Fernando Rocha, Artur Santos, Geber Ramalho, Veronica Teichrieb

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Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce GTS 360 M, Optimization, Path problems

December 23, 2011 by hgpu

Porting and optimizing MAGFLOW on CUDA

Giuseppe Bilotta, Eugenio Rustico, Alexis Herault, Annamaria Vicari, Giovanni Russo, Ciro Del Negro, Giovanni Gallo

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Tags: CUDA, Earth and Space Sciences, Geoscience, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization

December 21, 2011 by hgpu

Implementation of a Parallel Tree Method on a GPU

Naohito Nakasato

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Tags: Astrophysics, ATI, ATI IL, ATI Radeon HD 5870, Computational Complexity, Computer science, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, KD-tree, OpenCL, Optimization, Performance

December 21, 2011 by hgpu

Parallel Contour-Buildup Algorithm for the Molecular Surface

Michael Krone, Sebastian Grottel, Thomas Ertl

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Tags: Algorithms, Chemistry, CUDA, Molecular dynamics, Molecular surface, nVidia, nVidia GeForce GTX 580, Optimization, Pharmaceuticals, Visualization

December 20, 2011 by hgpu

Floating-point Mixed-radix FFT Core Generation for FPGA and Comparison with GPU and CPU

Bo Duan, Wendi Wang, Xingjian Li, Chunming Zhang, Peiheng Zhang, Ninghui Sun

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Tags: Algorithms, Computer science, CUDA, FFT, FPGA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 20, 2011 by hgpu

3D Recursive Gaussian IIR on GPU and FPGAs: A Case Study for Accelerating Bandwidth-Bounded Applications

Jason Cong, Muhuan Huang, Yi Zou

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Tags: CUDA, FPGA, Image processing, nVidia, Optimization, Tesla C1060

December 19, 2011 by hgpu

Optimization of mapped functions sequences using fusions on GPU

Jan Fousek

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 480, Optimization, Thesis

December 19, 2011 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Multilevel Tile Load Map on Massive Terrain Visualization

GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Image processing algorithm optimization with CUDA for Pure Data

GPU Pathfinding Optimization

Porting and optimizing MAGFLOW on CUDA

Implementation of a Parallel Tree Method on a GPU

Parallel Contour-Buildup Algorithm for the Molecular Surface

Floating-point Mixed-radix FFT Core Generation for FPGA and Comparison with GPU and CPU

3D Recursive Gaussian IIR on GPU and FPGAs: A Case Study for Accelerating Bandwidth-Bounded Applications

Optimization of mapped functions sequences using fusions on GPU

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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