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Region Templates: Data Representation and Management for Large-Scale Image Analysis

George Teodoro, Tony Pan, Tahsin Kurc, Jun Kong, Lee Cooper, Scott Klasky, Joel Saltz

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Tags: Computer science, CUDA, Heterogeneous systems, Hybrid computing, Microscopy, nVidia, OpenCV, Tesla M2090

June 2, 2014 by hgpu

GROMACS on Hybrid CPU-GPU and CPU-MIC Clusters: Preliminary Porting Experiences, Results and Next Steps

Sadaf Alam, Ugo Varetto

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Tags: Computer science, CUDA, GPU cluster, Hybrid computing, Intel Xeon Phi, MPI, nVidia, OpenCL, Tesla K20

February 12, 2014 by hgpu

Toward a Generic Hybrid CPU-GPU Parallelization of Divide-and-Conquer Algorithms

Alejandro Lopez-Ortiz, Alejandro Salinger, Robert Suderman

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Tags: Algorithms, ATI, ATI Radeon HD 5970, ATI Radeon HD 6530, Computer science, Heterogeneous systems, Hybrid computing, OpenCL

January 11, 2014 by hgpu

Efficient Large-Scale Graph Processing on Hybrid CPU and GPU Systems

Abdullah Gharaibeh, Elizeu Santos-Neto, Lauro Beltrao Costa, Matei Ripeanu

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, Hybrid computing, nVidia, Package

December 12, 2013 by hgpu

Hybrid Parallel Light-Weight Programming of Hybrid Systems

Frank Feinbube, Jan-Arne Sobania, Peter Troger, Andreas Polze

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Tags: Computer science, Hybrid computing, nVidia, nVidia GeForce GTX 460, OpenCL

October 27, 2013 by hgpu

GGAS: Global GPU Address Spaces for Efficient Communication in Heterogeneous Clusters

Lena Oden, Holger Froning

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Hybrid computing, Memory model, nVidia, nVidia Quadro 2000, nVidia Quadro FX 5800, Tesla K10, Tesla K20

October 25, 2013 by hgpu

Parallel Algorithms for Hybrid Multi-core CPU-GPU Implementations of Component Labelling in Critical Phase Models

K.A. Hawick, D.P. Playne

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Tags: Algorithms, CUDA, Hybrid computing, Numerical simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Phase transition, Physics, Tesla M2075, Tesla M2090

June 19, 2013 by hgpu

Scientific Computing on Hybrid Architectures

Marcus Holm

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Tags: Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 260, Tesla M2050, Thesis

June 7, 2013 by hgpu

C Language Extensions for Hybrid CPU/GPU Programming with StarPU

Ludovic Courtes

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Tags: Computer science, Hybrid computing, Mathematical Software, MPI, OpenCL, Package

April 4, 2013 by hgpu

Synchronization and Ordering Semantics in Hybrid MPI+GPU Programming

Ashwin M. Aji, Pavan Balaji, James Dinan, Wu-chun Feng, Rajeev Thakur

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Tags: Computer science, CUDA, Hybrid computing, MPI, nVidia, OpenCL, Tesla C2050

April 3, 2013 by hgpu

Prius: A Runtime for Hybrid Computing

Dominik Grewe

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Tags: Computer science, Heterogeneous systems, Hybrid computing, OpenCL

March 15, 2013 by hgpu

CPU and/or GPU: Revisiting the GPU Vs. CPU Myth

Kishore Kothapalli, Dip Sankar Banerjee, P. J. Narayanan, Surinder Sood, Aman Kumar Bahl, Shashank Sharma, Shrenik Lad, Krishna Kumar Singh, Kiran Matam, Sivaramakrishna Bharadwaj, Rohit Nigam, Parikshit Sakurikar, Aditya Deshpande, Ishan Misra, Siddharth Choudhary, Shubham Gupta

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Tags: Computer science, Databases, Hybrid computing, Image processing, nVidia, nVidia GeForce GT 520, Sparse matrix, Tesla T10

March 14, 2013 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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