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Agent-based crowd simulation using GPU computing

Sean Patrick O'Reilly

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Rendering, Thesis

July 28, 2014 by hgpu

CUDT: A CUDA Based Decision Tree Algorithm

Win-Tsung Lo, Yue-Shan Chang, Ruey-Kai Sheu, Chun-Chieh Chiu, Shyan-Ming Yuan

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Tags: Algorithms, Computer science, CUDA, Data mining, nVidia, nVidia GeForce 9800 GT

July 28, 2014 by hgpu

Towards fast and certified multiple-precision libraries

Valentina Popescu

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Tags: Algorithms, Computer science, CUDA, Extended precision, nVidia, Tesla C2075, Thesis

July 26, 2014 by hgpu

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

S.A. Arul Shalom, Manoranjan Dash

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce 8800 GTS

July 26, 2014 by hgpu

ReGen: Optimizing Genetic Selection Algorithms for Heterogeneous Computing

Scott Kenneth Winkleblack

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Tags: Computer science, CUDA, Genetic programming, Heterogeneous systems, nVidia, Tesla K20, Tesla K40, Thesis

July 26, 2014 by hgpu

ADHA: Automatic Data layout framework for Heterogeneous Architectures

Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar

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Tags: Benchmarking, Compilers, Computer science, Heterogeneous systems, nVidia, OpenCL, Programming Languages, Tesla M2050

July 24, 2014 by hgpu

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Kannappan Palaniappan

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Tags: Algorithms, Benchmarking, Cell processor, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Tesla C2070

July 24, 2014 by hgpu

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Istvan Zoltan Reguly

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Tags: Algorithms, Code generation, Computer science, CUDA, Differential equations, FEM, Finite element method, Finite volume method, Fluid dynamics, Heterogeneous systems, Linear Algebra, nVidia, Partial differential equations, PDEs, Programming techniques, Tesla C2070, Tesla K20, Tesla K40, Thesis

July 24, 2014 by hgpu

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

S. V. Ghorpade, S. M. Kamalapur

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Metaheuristics, nVidia, nVidia GeForce GTX 680, Search

July 23, 2014 by hgpu

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Koushik Mandal

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2075, Thesis

July 23, 2014 by hgpu

Faster Multipattern Matching System on GPU Based on Aho-Corasick Algorithm

Gaurav Bhamare, Satish Banait

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Security

July 23, 2014 by hgpu

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

M. Bader, A. Bode, H.-J. Bungartz

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Tags: Algorithms, Book, Computer science, CUDA, Heterogeneous systems, nVidia

July 22, 2014 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Agent-based crowd simulation using GPU computing

CUDT: A CUDA Based Decision Tree Algorithm

Towards fast and certified multiple-precision libraries

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

ReGen: Optimizing Genetic Selection Algorithms for Heterogeneous Computing

ADHA: Automatic Data layout framework for Heterogeneous Architectures

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Faster Multipattern Matching System on GPU Based on Aho-Corasick Algorithm

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

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