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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

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

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