high performance computing on graphics processing units: hgpu.org

Theses

hgpu.org » Applications

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Bartosz D. Wozniak

View

Download (PDF)

Source codes

Tags: CUBLAS, CUDA, Fluid dynamics, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Package, Python, Tesla K40, Thesis

July 7, 2014 by hgpu

Parallelization of the Symmetric Indefinite Factorization

Anastasia Kruchinina

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Factorization, Mathematics, Nonlinear optimization, nVidia, Tesla S2050, Thesis

July 7, 2014 by hgpu

Fast and Efficient Lossless Image Compression Based on CUDA Parallel Wavelet Tree Encoding

Jingqi Ao

View

Download (PDF)

Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GTX 570, Thesis, Wavelet

July 7, 2014 by hgpu

High-level Parallel Programming Support for Heterogeneous Systems

Bo Wu

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Tesla C2050, Thesis

July 6, 2014 by hgpu

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Guillaume Chapuis

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, CUDA, Genetics, Graph theory, nVidia, Path problems, Tesla C2050, Thesis

July 3, 2014 by hgpu

High-Level Programming Framework for Executing Streaming Applications on Heterogeneous OpenCL Platforms

Matthias Baer

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7750, Computer science, Heterogeneous systems, OpenCL, Thesis

July 1, 2014 by hgpu

Performance and Efficiency Analysis of Modern Accelerators: Fine-Grained Parallelism on the Intel Xeon Phi

Robrecht Dewaele

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, Intel Xeon Phi, Package, Performance, Thesis

June 28, 2014 by hgpu

Industrial Robot Collision Handling in Harsh Environments

Knut Berg Kaldestad

View

Download (PDF)

Tags: Algorithms, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 680, Thesis

June 27, 2014 by hgpu

C and CUDA Implementation for SIRT and SART Reconstruction Algorithms

Shan He

View

Download (PDF)

Tags: CUDA, Image processing, Image reconstruction, nVidia, nVidia GeForce GTX 660, Thesis

June 26, 2014 by hgpu

GPU-Parallel simulation of rigid fibers in Stokes flow

Ronny Eriksson

View

Download (PDF)

Tags: Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 260, Thesis

June 25, 2014 by hgpu

AES encryption on modern consumer architectures

Lupescu Grigore

View

Download (PDF)

Tags: AES, AMD Radeon R7 250, ATI, Computer science, cpu, GPU, OpenCL, Security, Thesis

June 24, 2014 by glupescu

Feature Generation for Quantification of Visual Similarity

Tianning Steven Han

View

Download (PDF)

Tags: Algorithms, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla K20, Thesis

June 23, 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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Theses

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Parallelization of the Symmetric Indefinite Factorization

Fast and Efficient Lossless Image Compression Based on CUDA Parallel Wavelet Tree Encoding

High-level Parallel Programming Support for Heterogeneous Systems

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

High-Level Programming Framework for Executing Streaming Applications on Heterogeneous OpenCL Platforms

Performance and Efficiency Analysis of Modern Accelerators: Fine-Grained Parallelism on the Intel Xeon Phi

Industrial Robot Collision Handling in Harsh Environments

C and CUDA Implementation for SIRT and SART Reconstruction Algorithms

GPU-Parallel simulation of rigid fibers in Stokes flow

AES encryption on modern consumer architectures

Feature Generation for Quantification of Visual Similarity

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

Most viewed papers (last 30 days)