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An Effective Model of CPU/GPU Collaborative Computing in GPU Clusters

Yue Gu, Jian-Hua Gu, Xing-She Zhou

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Tags: Algorithms, Computer science, CUDA, GPU cluster, nVidia, Tesla C2050

April 4, 2015 by hgpu

The Design and Implementation of a Verification Technique for GPU Kernels

Adam Betts, Nathan Chong, Alastair F. Donaldson, Jeroen Ketema, Shaz Qadeer, Paul Thomson, John Wickerson

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Tags: ARM, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C2050

April 4, 2015 by hgpu

Using OpenCL to Implement Median Filtering and RSA Algorithms: Two GPGPU Application Case Studies

Lukas Gillsjo

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Tags: Algorithms, ATI, ATI Radeon R9 280X, Computer science, Filtering, Image processing, nVidia, OpenCL, RSA, Security, Tesla M2050, Thesis

April 4, 2015 by hgpu

Generating Null Models for Large-Scale Networks on GPU

Huan Li, Gang Lu, Junxia Guo

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Tags: C++ AMP, Computer science, Networks, nVidia, nVidia GeForce GTX 480

April 1, 2015 by hgpu

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

J. Briggs, J. Jaykka, J. R. Fergusson, E. P. S. Shellard, S. J. Pennycook

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Tags: Astrophysics, Computer science, Intel Xeon Phi, MPI, OpenMP

April 1, 2015 by hgpu

Massively Parallel Analysis of Similarity Matrices on Heterogeneous Hardware

Tobias Rawald, Mike Sips, Norbert Marwan, Ulf Leser

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Tags: ATI, ATI Radeon HD 7470, Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 690, OpenCL

March 30, 2015 by hgpu

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

Dayong Wang, Anil K. Jain

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, Filtering, Machine learning, Neural networks, nVidia, Tesla K20

March 30, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

Loo.py: From Fortran to performance via transformation and substitution rules

Andreas Klockner

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Tags: Code generation, Computer science, Fortran, OpenCL, Package, Python

March 28, 2015 by hgpu

Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures

Guillaume Chapuis, Hristo Djidjev

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Tags: Computer science, Data Structures and Algorithms, Distributed computing, Distributed data structures, GPU cluster, nVidia, Path problems, Tesla M2090

March 28, 2015 by hgpu

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Xiaowen Chu, Chengjian Liu, Kai Ouyang, Ling Sing Yung, Hai Liu, Yiu-Wing Leung

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Tags: Computer science, CUDA, Error recovery, nVidia, nVidia GeForce GTX 780

March 28, 2015 by hgpu

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Vadim Demchik

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 560 M, nVidia GeForce GTX 780, OpenCL, Package, Pseudo-random number generators, Review, Tesla K40

March 25, 2015 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

An Effective Model of CPU/GPU Collaborative Computing in GPU Clusters

The Design and Implementation of a Verification Technique for GPU Kernels

Using OpenCL to Implement Median Filtering and RSA Algorithms: Two GPGPU Application Case Studies

Generating Null Models for Large-Scale Networks on GPU

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

Massively Parallel Analysis of Similarity Matrices on Heterogeneous Hardware

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Loo.py: From Fortran to performance via transformation and substitution rules

Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

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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