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Keeneland: Bringing heterogeneous GPU computing to the computational science community

Jeffrey S. Vetter, Richard Glassbrook, Jack Dongarra, Karsten Schwan, Bruce Loftis, Stephen McNally, Jeremy Meredith, James Rogers, Philip Roth Kyle Spafford, Sudhakar Yalamanchili

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Tags: Computer science, Hardware Architecture, Heterogeneous systems, nVidia, Tesla M2070

November 7, 2011 by hgpu

Vergence Using GPU Cepstral Filtering

Luis Almeida, Paulo Menezes, Jorge Dias

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Tags: Algorithms, Computer science, Computer vision, CUDA, Filtering, nVidia, nVidia GeForce 9800 GTX

November 7, 2011 by hgpu

GPU-accelerated Convex Multi-phase Image Segmentation

Subrahmanyam Gorthi, Arnaud Le Carvennec, Hadrien Copponnex, Xavier Bresson, Jean-Philippe Thiran

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Source codes

Tags: Algorithms, Computational Complexity, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 285, Optimization, Package

November 7, 2011 by hgpu

Parallelization of algorithms for solving the Boltzmann equation for GPU-based computations

E.A. Malkov, M.S. Ivanov

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Tags: Algorithms, Boltzmann equation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Physics

November 6, 2011 by hgpu

The conjugate gradient solver accelerated by GPU for solving wave-propagation problems

Chao Chen

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, Linear Algebra, Matrix multiplication, nVidia

November 6, 2011 by hgpu

Fast QAP Solver with ACO and Taboo Search on GPU using Move-Cost Adjusted Thread Assignment

Shigeyoshi Tsutsui, Noriyuki Fujimoto

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 480, Search

November 5, 2011 by hgpu

Challenges for compiler support for exascale computing

Daniel Quinlan

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Tags: Compilers, Computer science, CUDA, nVidia, Optimization, Presentation

November 5, 2011 by hgpu

CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

Evert van Aart, Neda Sepasian, Andrei Jalba, Anna Vilanova

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Tags: Algorithms, Computer science, CUDA, Diffusion tensor, nVidia, nVidia GeForce GTX 470, Raytracing

November 5, 2011 by hgpu

A mobile robot navigation with use of CUDA parallel architecture

Barbara Siemiatkowska, Jacek Szklarski, Michal Gnatowski, Adam Borkowski, Piotr Weclewski

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9300 M, Sensing

November 5, 2011 by hgpu

Real-time Flame Rendering with GPU and CUDA

Wei Wei,Yanqiong Huang

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Tags: 3D Graphics and Realism, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce 7600 GS, OpenGL, Particle simulation, Rendering

November 5, 2011 by hgpu

PEPSC: A Power-Efficient Processor for Scientific Computing

Ganesh Dasika, Ankit Sethia, Trevor Mudge, Scott Mahlke

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Tags: Computer science, Energy-efficient computing, Hardware Architecture, nVidia, nVidia GeForce GTX 285, Prefetch

November 4, 2011 by hgpu

Semi-Global Matching-Motivation, Developments and Applications

Heiko Hirschmuller

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Tags: Computer science, Computer vision, FPGA, nVidia, nVidia GeForce GTX 275, OpenCL, OpenGL, Sensing

November 4, 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

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high performance computing on graphics processing units: hgpu.org

Keeneland: Bringing heterogeneous GPU computing to the computational science community

Vergence Using GPU Cepstral Filtering

GPU-accelerated Convex Multi-phase Image Segmentation

Parallelization of algorithms for solving the Boltzmann equation for GPU-based computations

The conjugate gradient solver accelerated by GPU for solving wave-propagation problems

Fast QAP Solver with ACO and Taboo Search on GPU using Move-Cost Adjusted Thread Assignment

Challenges for compiler support for exascale computing

CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

A mobile robot navigation with use of CUDA parallel architecture

Real-time Flame Rendering with GPU and CUDA

PEPSC: A Power-Efficient Processor for Scientific Computing

Semi-Global Matching-Motivation, Developments and Applications

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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