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Parallel Computing: The Elephant in the Room

Patrick H. Madden

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Tags: Algorithms, Computer science, Performance, Review

March 5, 2011 by hgpu

Inter-Block GPU Communication via Fast Barrier Synchronization

Shucai Xiao, Wu-chun Feng

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 280, Performance, Sorting

March 5, 2011 by hgpu

Designing Efficient Many-Core Parallel Algorithms for All-Pairs Shortest-Paths Using CUDA

Quoc-Nam Tran

Tags: Algorithms, Computer science, CUDA, nVidia, Path problems

March 5, 2011 by hgpu

Smooth Mixed-Resolution GPU Volume Rendering

Johanna Beyer, Markus Hadwiger, Torsten Moller, Laura Fritz

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 280, OpenGL, Rendering, Visualization

March 3, 2011 by hgpu

The sparse matrix vector product on GPUs

F. Vazquez, E. M. Garzon , J. A. Martinez, J. J. Fernandez

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Sparse matrix

March 3, 2011 by hgpu

Speeding Up Cycle Based Logic Simulation Using Graphics Processing Units

Alper Sen, Baris Aksanli, Murat Bozkurt

Tags: Algorithms, Computer science, CUDA, Electronic design automation, Graph theory, nVidia

March 3, 2011 by hgpu

Real-time dynamic tone-mapping operator on GPU

Mohamed Akil, Thierry Grandpierre, Laurent Perroton

Tags: Algorithms, Image processing, nVidia, nVidia GeForce 8800 GTX

March 3, 2011 by hgpu

FluoroSim: A Visual Problem-Solving Environment for Fluorescence Microscopy

Cory W. Quammen, Alvin C. Richardson, Julian Haase, Benjamin D. Harrison, Russell M. Taylor, Kerry S. Bloom

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Tags: Algorithms, Biology, CUDA, Image generation, Microscopy, nVidia, nVidia GeForce 8800 GTX, OpenGL, Package

March 2, 2011 by hgpu

Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

Muthu Manikandan Baskaran, Uday Bondhugula, Sriram Krishnamoorthy, J. Ramanujam, Atanas Rountev, P. Sadayappan

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Performance

February 28, 2011 by hgpu

Efficient hierarchical parallel genetic algorithms using grid computing

Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee

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Tags: Algorithms, Computer science, Genetic programming, Grid

February 27, 2011 by hgpu

Accelerating CUDA Graph Algorithms at Maximum Warp

Sungpack Hong, Sang Kyun Kim, Tayo Oguntebi, Kunle Olukotun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, Package, Performance, Programming techniques

February 27, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

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Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 2011 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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel Computing: The Elephant in the Room

Inter-Block GPU Communication via Fast Barrier Synchronization

Designing Efficient Many-Core Parallel Algorithms for All-Pairs Shortest-Paths Using CUDA

Smooth Mixed-Resolution GPU Volume Rendering

The sparse matrix vector product on GPUs

Speeding Up Cycle Based Logic Simulation Using Graphics Processing Units

Real-time dynamic tone-mapping operator on GPU

FluoroSim: A Visual Problem-Solving Environment for Fluorescence Microscopy

Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

Efficient hierarchical parallel genetic algorithms using grid computing

Accelerating CUDA Graph Algorithms at Maximum Warp

A Tuning Framework for Software-Managed Memory Hierarchies

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

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

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