Machine learning | Page 57

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Approximate Principal Direction Trees

Mark McCartin-Lim, Andrew McGregor, Rui Wang

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Tags: Computer science, Data Structures and Algorithms, Machine learning, nVidia, nVidia GeForce GTX 470

June 25, 2012 by hgpu

An Investigation into Concurrent Expectation Propagation

David Hall, Alex Kantchelian

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Tags: Algorithms, ATI, ATI Radeon HD 6490 M, Computer science, Machine learning, OpenCL, Physics

June 20, 2012 by hgpu

Genetic Algorithm Modeling with GPU Parallel Computing Technology

S. Cavuoti, M. Garofalo, M. Brescia, A. Pescape, G. Longo, G. Ventre

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Tags: Algorithms, Astrophysics, Computer science, CUDA, Data mining, Genetic programming, Machine learning, nVidia, nVidia GeForce GT 540 M

April 21, 2012 by hgpu

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

James Bergstra, Nicolas Pinto, David Cox

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Tags: Computer science, CUDA, Filtering, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Optimization, Tesla C1060, Tesla C2070

March 29, 2012 by hgpu

GPU Computing for Machine Learning Algorithms

Mauro Garofalo

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GT 540 M, Thesis

February 28, 2012 by hgpu

CudaRF: A CUDA-based Implementation of Random Forests

Hakan Grahn, Niklas Lavesson, Mikael Hellborg Lapajne, Daniel Slat

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Data mining, Machine learning, nVidia, nVidia GeForce GT 220

February 9, 2012 by hgpu

Analysis Acceleration in TMVA for the ATLAS Experiment at CERN using GPU Computing

Hazel McKendrick

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Tags: CUDA, High Energy Physics - Experiment, Machine learning, Neural networks, nVidia, Physics, Tesla C1060, Tesla C2050, Thesis

January 23, 2012 by hgpu

Leveraging on High-Performance Computing and Cloud Technologies in Digital Libraries: A Case Study

Peter Wittek, Sandor Daranyi

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Tags: Algorithms, Cloud, Computer science, Machine learning, MapReduce, Text mining

January 20, 2012 by hgpu

Combining approximate inference methods for efficient learning on large computer clusters

Zhenwen Dai, Jacquelyn A. Shelton, Jorg Bornschein, Abdul Saboor Sheikh, Jorg Lucke

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Tags: Algorithms, Computational Complexity, Computer science, GPU cluster, Machine learning, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Python

January 19, 2012 by hgpu

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

Haixiang Shi, Bertil Schmidt, Weiguo Liu, Wolfgang Muller-Wittig

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Source codes

Tags: Algorithms, Biology, Computational biology, CUDA, Image processing, Machine learning, nVidia, Package, Tesla C2050

January 13, 2012 by hgpu

Torch7: A Matlab-like Environment for Machine Learning

Ronan Collobert, Koray Kavukcuoglu, Clement Farabet

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 460

December 31, 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

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

See all packages

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high performance computing on graphics processing units: hgpu.org

Approximate Principal Direction Trees

An Investigation into Concurrent Expectation Propagation

Genetic Algorithm Modeling with GPU Parallel Computing Technology

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

GPU Computing for Machine Learning Algorithms

CudaRF: A CUDA-based Implementation of Random Forests

Analysis Acceleration in TMVA for the ATLAS Experiment at CERN using GPU Computing

Combining approximate inference methods for efficient learning on large computer clusters

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

Torch7: A Matlab-like Environment for Machine Learning

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

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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