high performance computing on graphics processing units: hgpu.org

Theses

hgpu.org » Applications

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

Youssef S. G. Nashed

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GT 630 M, nVidia GeForce GTS 450, Pattern recognition, Thesis

August 23, 2014 by hgpu

GPU accelerated rendering of vector based maps on iOS

Jonas Bromo, Alexander Qvick Faxa

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Tags: Computer science, OpenGL, Optimization, Rendering, Thesis, Visualization

August 21, 2014 by hgpu

Error Resilience Evaluation on GPGPU Applications

Bo Fang

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Tags: Algorithms, Computer science, CUDA, Fault tolerance, nVidia, Package, Thesis

August 21, 2014 by hgpu

Graphics Processing Unit Bloom Filters: Classical and Probabilistic

Joshua Michael Pyle

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Tags: Bloom filter, Computer science, CUDA, Data Structures and Algorithms, Databases, nVidia, nVidia GeForce GT 620, Security, Thesis

August 13, 2014 by hgpu

Accelerating Fruchterman-Reingold with OpenCL

Gerrit Krijnen

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GT 740 M, OpenCL, Rendering, Thesis, Visualization

August 11, 2014 by hgpu

Optimising Purely Functional GPU Programs (Thesis)

Trevor L. McDonell

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Performance, Tesla T10, Thesis

August 10, 2014 by hgpu

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA CUDA

Mehran Maghoumi

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Tags: Computer science, Computer vision, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 660, Package, Thesis

August 9, 2014 by hgpu

Optimizing memory management on heterogeneous systems using polyhedral, compile-time techniques

Vassilis Vassiliadis

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Tags: Computer science, Heterogeneous systems, Memory model, OpenCL, Package, Thesis

August 7, 2014 by hgpu

Multi-Threaded Automatic Integration Using OpenMP and CUDA

Rida Assaf

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Tags: Computational finance, Computer science, CUDA, Finance, Monte Carlo integration, nVidia, OpenMP, Physics, Tesla K20, Thesis

August 3, 2014 by hgpu

Discriminative Convolutional Sum-Product Networks on GPU

Tobias Hartmann

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Tags: Algorithms, Benchmarking, Computer science, Computer vision, CUDA, Neural networks, nVidia, Tesla K20, Thesis

August 1, 2014 by hgpu

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Peng Di

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tesla C2050, Thesis

July 30, 2014 by hgpu

Optimizing Lempel-Ziv Factorization for the GPU Architecture

Bryan Ching

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Tags: Algorithms, Compression, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX Titan, Tesla K40, Thesis

July 29, 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

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

BoltzGen:Toward Universal Binder Design

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

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high performance computing on graphics processing units: hgpu.org

Theses

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

GPU accelerated rendering of vector based maps on iOS

Error Resilience Evaluation on GPGPU Applications

Graphics Processing Unit Bloom Filters: Classical and Probabilistic

Accelerating Fruchterman-Reingold with OpenCL

Optimising Purely Functional GPU Programs (Thesis)

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA CUDA

Optimizing memory management on heterogeneous systems using polyhedral, compile-time techniques

Multi-Threaded Automatic Integration Using OpenMP and CUDA

Discriminative Convolutional Sum-Product Networks on GPU

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Optimizing Lempel-Ziv Factorization for the GPU Architecture

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

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

BoltzGen:Toward Universal Binder Design

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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