high performance computing on graphics processing units: hgpu.org

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GPU-Based Liquid Crystal Display Processing Platform

Song Peng

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Tags: Algorithms, CUDA, Image generation, Image processing, nVidia, nVidia Quadro FX 580, Thesis

December 6, 2011 by hgpu

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

Alecio Pedro Delazari Binotto

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, OpenCL, Task scheduling, Thesis

December 5, 2011 by hgpu

Scalable Query Evaluation in Relational Databases

Rasmus Resen Amossen

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Tags: Algorithms, Computer science, Databases, Matrix multiplication, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Python, Thesis

December 5, 2011 by hgpu

Solving Rigid Multibody Physics Dynamics Using Proximal Point Functions on the GPU

Jeremy James Betz

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Tags: CUDA, nVidia, nVidia GeForce GTX 480, Physics, Thesis

December 4, 2011 by hgpu

On the design of architecture-aware algorithms for emerging applications

Seunghwa Kang

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Source codes

Tags: Algorithms, Benchmarking, Biology, Cell processor, Computational biology, CUDA, Image processing, MapReduce, nVidia, Package, Tesla C1060, Thesis

December 2, 2011 by hgpu

Evaluation of Fermi Features for Data Mining Algorithms

Sinduja Muralidharan

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, Nearest neighbour, nVidia, Tesla C1060, Tesla C2050, Thesis

December 2, 2011 by hgpu

Multiresolution Flow Simulations on Multi/many-core Architectures

Diego Rossinelli

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Tags: Algorithms, Computational Complexity, CUDA, Differential equations, Fluid dynamics, Heterogeneous systems, nVidia, Partial differential equations, PDEs, Tesla S1070, Tesla T10, Thesis, Wavelet

November 29, 2011 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

Directives Based Programming of GPU Accelerated Systems

Saif Mulla

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Tags: Computer science, CUDA, Molecular dynamics, nVidia, Programming techniques, Tesla C2050, Thesis

November 29, 2011 by hgpu

Enabling Efficient Online Profiling of Homogeneous and Heterogeneous Multicore Systems

Dan Upton

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

November 29, 2011 by hgpu

A hybrid parallel framework for computational solid mechanics

Piotr Fidkowski

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Tags: CUDA, Hybrid computing, MPI, nVidia, Physics, Tesla C1060, Thesis

November 28, 2011 by hgpu

Molecular Dynamics Simulation Based on Hadoop MapReduce

Chen He

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Tags: Chemistry, Cluster computing, CUDA, MapReduce, Molecular dynamics, nVidia, nVidia GeForce 9400 GT, Physics, Thesis

November 28, 2011 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

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

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

GPU-Based Liquid Crystal Display Processing Platform

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

Scalable Query Evaluation in Relational Databases

Solving Rigid Multibody Physics Dynamics Using Proximal Point Functions on the GPU

On the design of architecture-aware algorithms for emerging applications

Evaluation of Fermi Features for Data Mining Algorithms

Multiresolution Flow Simulations on Multi/many-core Architectures

Applications Performance on GPGPUs with the Fermi Architecture

Directives Based Programming of GPU Accelerated Systems

Enabling Efficient Online Profiling of Homogeneous and Heterogeneous Multicore Systems

A hybrid parallel framework for computational solid mechanics

Molecular Dynamics Simulation Based on Hadoop MapReduce

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

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

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

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