high performance computing on graphics processing units: hgpu.org

hgpu.org » Thesis

Performance Optimization of GPU ELF-Codes

Fausto Artico

Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, PTX, Tesla C2070, Thesis

May 15, 2014 by hgpu

Implementation of a distributed real-time video panorama pipeline for creating high quality virtual views

Ragnar Langseth

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 680, Thesis

May 12, 2014 by hgpu

Dynamic Orchestration of Massively Data Parallel Execution

Mehrzad Samadi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 560, OpenCL, Performance, Tesla C2050, Thesis

May 10, 2014 by hgpu

Applying Source Level Auto-Vectorization to Aparapi Java

Frank Curtis Albert

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Tags: Computer science, CUDA, Java, nVidia, nVidia GeForce GTX Titan, OpenCL, Thesis

May 9, 2014 by hgpu

Learning Sparse Recurrent Neural Networks in Language Modeling

Yuanlong Shao

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan, Thesis

May 7, 2014 by hgpu

Improving the Programmability of GPU Architectures

Cedric Nugteren

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenACC, OpenCL, Package, Performance, Thesis

May 7, 2014 by hgpu

Orchestrating Thread Scheduling and Cache Management to Improve Memory System Throughput in Throughput Processors

Dong Li

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Tags: Computer science, GPGPU-sim, Performance, Thesis

May 7, 2014 by hgpu

Bio-Inspired Optimization of Ultra-Wideband Patch Antennas Using Graphics Processing Unit Acceleration

Brian Vyhnalek

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Tags: Artificial intelligence, ATI, ATI Radeon HD 6450, Computer science, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, OpenCL, Particle swarm optimization, Thesis

May 7, 2014 by hgpu

Accelerating Cryptosystems on Hardware Platforms

Wei Wang

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Tags: Cloud, Computer science, CUDA, FFT, nVidia, RSA, Security, Tesla C2050, Thesis

May 6, 2014 by hgpu

Multireduce and Multiscan on Modern GPUs

Marco Eilers

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 690, Sorting, Thesis

May 6, 2014 by hgpu

Computer vision for continuous plankton monitoring

Damian Janusz Matuszewski

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Tags: Computer science, Computer vision, CUDA, Data acquisition, nVidia, nVidia GeForce GTX 480, OpenCV, Thesis

May 5, 2014 by hgpu

Accelerating Mixed-Abstraction SystemC Models on Multi-Core CPUs and GPUs

Anirudh Mohan Kaushik

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla C2075, Thesis

May 5, 2014 by hgpu

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

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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Performance Optimization of GPU ELF-Codes

Implementation of a distributed real-time video panorama pipeline for creating high quality virtual views

Dynamic Orchestration of Massively Data Parallel Execution

Applying Source Level Auto-Vectorization to Aparapi Java

Learning Sparse Recurrent Neural Networks in Language Modeling

Improving the Programmability of GPU Architectures

Orchestrating Thread Scheduling and Cache Management to Improve Memory System Throughput in Throughput Processors

Bio-Inspired Optimization of Ultra-Wideband Patch Antennas Using Graphics Processing Unit Acceleration

Multireduce and Multiscan on Modern GPUs

Computer vision for continuous plankton monitoring

Accelerating Mixed-Abstraction SystemC Models on Multi-Core CPUs and GPUs

Recent source codes

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

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

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