high performance computing on graphics processing units: hgpu.org

Theses

hgpu.org » Applications

Acceleration Methods for Bayesian Network Sampling

Haohai Yu

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Bayesian, Benchmarking, Clustering, Computer science, OpenCL, Probability, Thesis

November 2, 2011 by hgpu

A Real-Time Computer Vision Library for Heterogeneous Processing Environments

Tony J. Liu

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Tags: Computer science, Computer vision, DSP, FPGA, Heterogeneous systems, Package, Thesis

November 1, 2011 by hgpu

GPU Computations in Heterogeneous Grid Environments

Marcus Hinders

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Tags: ATI, ATI Radeon HD 5870, Biology, Computational biology, Computer science, Grid, Heterogeneous systems, nVidia, nVidia GeForce 8600 GT, nVidia GeForce GTX 280, OpenCL, Thesis

October 30, 2011 by hgpu

CPU and GPU Co-processing for Sound

Aleksander Gjermundsen

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Filtering, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Signal processing, Tesla C2050, Thesis

October 30, 2011 by hgpu

Jit4OpenCL: a compiler from Python to OpenCL

Xunhao Li

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Tags: ATI, ATI Radeon HD 5850, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, OpenCL, Python, Thesis

October 29, 2011 by hgpu

Using OpenCL for image analysis

Niklas Frisk

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Tags: Algorithms, Benchmarking, Image processing, Java, nVidia, nVidia GeForce 8600 M, OpenCL, Thesis

October 29, 2011 by hgpu

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 2011 by hgpu

Compiling Stream Applications for Heterogeneous Architectures

Amir H. Hormati

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Tags: Compilers, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Optimization, Tesla C2050, Thesis

October 28, 2011 by hgpu

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Giovanni Ansaloni

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Tags: Algorithms, Computer science, Design space exploration, Heterogeneous systems, Thesis

October 28, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Techniques to maximize memory bandwidth on the Rigel compute accelerator

William J. Tuohy

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Tags: ATI, ATI Radeon HD 5870, Computer science, Memory, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10, Thesis

October 27, 2011 by hgpu

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Robert Hegner

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package, Thesis

October 27, 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

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high performance computing on graphics processing units: hgpu.org

Theses

Acceleration Methods for Bayesian Network Sampling

A Real-Time Computer Vision Library for Heterogeneous Processing Environments

GPU Computations in Heterogeneous Grid Environments

CPU and GPU Co-processing for Sound

Jit4OpenCL: a compiler from Python to OpenCL

Using OpenCL for image analysis

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Compiling Stream Applications for Heterogeneous Architectures

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Matrix inversion speed up with CUDA

Techniques to maximize memory bandwidth on the Rigel compute accelerator

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

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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