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The K-Anonymity Approach in Preserving the Privacy of E-Services that Implement Data Mining

Ion Lungu, Alexandru Pirjan

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Tags: Algorithms, CUDA, Data mining, Databases, Finance, nVidia, nVidia GeForce GTX 480

November 24, 2011 by hgpu

The Optimization of Algorithms in the Process of Temporal Data Mining Using the Compute Unified Device Architecture

Alexandru Pirjan

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Tags: Algorithms, Computer science, CUDA, Data mining, MapReduce, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Review

November 24, 2011 by hgpu

A Parallel Deconvolution Algorithm in Perfusion Imaging

Fan Zhu, David Rodriguez Gonzalez, Trevor Carpenter, Malcolm Atkinson, Joanna Wardlaw

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Tags: Algorithms, Biology, CUDA, Medicine, nVidia, nVidia GeForce GTX 280, Performance, Tesla C1060

November 23, 2011 by hgpu

Towards solving the Table Maker’s Dilemma on GPU

Pierre Fortin, Mourad Gouicem, Stef Graillat

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, Tesla C2070

November 23, 2011 by hgpu

Accelerating Protein Sequence Search in a Heterogeneous Computing System

Shucai Xiao, Heshan Lin, Wu-chun Feng

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Tags: Algorithms, Bioinformatics, Biology, BLAST, Databases, Heterogeneous systems, nVidia, Optimization, Tesla C1060, Tesla C2050

November 23, 2011 by hgpu

An efficient mixed-precision, hybrid CPU-GPU implementation of a fully implicit particle-in-cell algorithm

Guangye Chen, Luis Chacon, Daniel C. Barnes

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Tags: Algorithms, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 580, Optimization, Particle-in-cell methods, Physics, Plasma physics

November 23, 2011 by hgpu

Application of GPGPU for Acceleration of Short DNA Sequence Alignment in Unipro UGENE Project

Konstantin Okonechinkov, German Grekhov, Konstantin Stepanyuk, Mikhail Fursov

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Tags: Algorithms, Bioinformatics, Biology, nVidia, OpenCL, Package, Sequence alignment, Tesla C1060, Tesla C2070

November 22, 2011 by hgpu

GPU-based Multi-start Local Search Algorithms

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 280, Optimization, Search

November 22, 2011 by hgpu

CT image reconstruction with half precision floating-point values

Clemens Maass, Sven Steckmann, Matthias Baer, Lars Hillebrand, Willi A. Kalender, Marc Kachelriess

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Tags: Algorithms, Computed tomography, CT, CUDA, Image processing, Image reconstruction, Larrabee, Medicine, nVidia, nVidia GeForce GTX 280

November 21, 2011 by hgpu

Efficient GPGPU-based parallel packet classification

Che-Lun Hung, Yaw-Ling Lin, Kuan-Ching Li, Hsiao-Hsi Wang, Shih-Wei Guo

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Tags: Algorithms, Computer science, CUDA, Filtering, Network communications, nVidia, nVidia GeForce GTS 450, Security

November 21, 2011 by hgpu

Conflux: Embedding Massively Parallel Semantics in a High-Level Programming Language

Eugene Burmako, Rauf Sadykhov

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Tags: Algorithms, Computer science, CUDA, High-level Languages, nVidia, Package

November 21, 2011 by hgpu

Graph-based Parallel Analysis of Large Analog Circuits Based on GPU Platforms

Jianan Lu, Zhigang Hao, Sheldon X.-D. Tan

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Tags: Algorithms, CAD, Computer science, CUDA, Electronic design automation, Graph theory, nVidia, Tesla S1070

November 21, 2011 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

The K-Anonymity Approach in Preserving the Privacy of E-Services that Implement Data Mining

The Optimization of Algorithms in the Process of Temporal Data Mining Using the Compute Unified Device Architecture

A Parallel Deconvolution Algorithm in Perfusion Imaging

Towards solving the Table Maker’s Dilemma on GPU

Accelerating Protein Sequence Search in a Heterogeneous Computing System

An efficient mixed-precision, hybrid CPU-GPU implementation of a fully implicit particle-in-cell algorithm

Application of GPGPU for Acceleration of Short DNA Sequence Alignment in Unipro UGENE Project

GPU-based Multi-start Local Search Algorithms

CT image reconstruction with half precision floating-point values

Efficient GPGPU-based parallel packet classification

Conflux: Embedding Massively Parallel Semantics in a High-Level Programming Language

Graph-based Parallel Analysis of Large Analog Circuits Based on GPU Platforms

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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