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Using the High Productivity Language Chapel to Target GPGPU Architectures

Albert Sidelnik, Maria J. Garzaran, David Padua, Bradford L. Chamberlain

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 280, Optimization

November 19, 2011 by hgpu

Exploiting concurrent kernel execution on graphic processing units

Lingyuan Wang, Miaoqing Huang, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla C2070

November 19, 2011 by hgpu

Towards Faster Cloth Simulation: Examining the Preconditioned Conjugate Gradient

Konstantinos Sideris

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Tags: 3D Graphics and Realism, Algorithms, Computer science, OpenCL, Pthreads

November 19, 2011 by hgpu

Towards Efficient GPU Sharing on Multicore Processors

Lingyuan Wang, Miaoqing Huang, Tarek El-Ghazawi

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Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Programming techniques, Tesla C1060, Tesla C2070

November 19, 2011 by hgpu

ShoveRand: a model-driven framework to easily generate random numbers on GP-GPU

Jonathan Passerat-Palmbach, Claude Mazel, David R.C. Hill

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Tags: Computer science, CUDA, nVidia, Pseudo-random number generators, Stochastic simulation, Tesla C1060

November 19, 2011 by hgpu

SGPU 2: a runtime system for using large applications on clusters of hybrid nodes

Matthieu Ospici, Dimitri Komatitsch, Jean-Francois Mehaut, Thierry Deutsch

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Tags: Benchmarking, Computer science, CUDA, Hybrid computing, nVidia, Tesla T10

November 19, 2011 by hgpu

Predictive Modeling and Analysis of OP2 on Distributed Memory GPU Clusters

G.R. Mudalige, M.B. Giles, C. Bertolli, P.H.J Kelly

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Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 560 Ti, Performance, Tesla C2070

November 19, 2011 by hgpu

Teaching graphics processing and architecture using a hardware prototyping approach

Michael Steffen, Phillip Jones, Joseph Zambreno

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Tags: Algorithms, Computer science, Education, FPGA, OpenGL, Rendering

November 19, 2011 by hgpu

StreamMR: An Optimized MapReduce Framework for AMD GPUs

Marwa Elteir, Heshan Lin, Wu-chun Feng, Tom Scogland

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, MapReduce, OpenCL

November 19, 2011 by hgpu

Design and Implementation of a PTX Emulation Library

Albert Claret Exojo

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Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Performance, PTX, Tesla S870, Thesis

November 18, 2011 by hgpu

Particle-based Visualization of Large Cosmological Datasets

Niko Lukac

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Tags: ATI, ATI Radeon HD 5750, Computer science, Cosmology, OpenGL, Rendering, Visualization

November 18, 2011 by hgpu

The MOPED framework: Object recognition and pose estimation for manipulation

The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA

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Tags: Algorithms, Clustering, Computer science, Computer vision, nVidia, nVidia GeForce GTX 260, Package, SIFT

November 18, 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

Using the High Productivity Language Chapel to Target GPGPU Architectures

Exploiting concurrent kernel execution on graphic processing units

Towards Faster Cloth Simulation: Examining the Preconditioned Conjugate Gradient

Towards Efficient GPU Sharing on Multicore Processors

ShoveRand: a model-driven framework to easily generate random numbers on GP-GPU

SGPU 2: a runtime system for using large applications on clusters of hybrid nodes

Predictive Modeling and Analysis of OP2 on Distributed Memory GPU Clusters

Teaching graphics processing and architecture using a hardware prototyping approach

StreamMR: An Optimized MapReduce Framework for AMD GPUs

Design and Implementation of a PTX Emulation Library

Particle-based Visualization of Large Cosmological Datasets

The MOPED framework: Object recognition and pose estimation for manipulation

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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