high performance computing on graphics processing units: hgpu.org

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Intra-node Memory Safe GPU Co-Scheduling

Carlos Reano, Federico Silla, Dimitrios S. Nikolopoulos, Blesson Varghese

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Tags: Computer science, CUDA, nVidia, Package, Task scheduling, Tesla K20

December 15, 2017 by hgpu

On algorithmic reductions in task-parallel programming models

Jan Ciesko

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Tags: Computer science, Intel Xeon Phi, OpenMP, Package, Thesis

December 10, 2017 by hgpu

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Qualcomm Technologies, Inc

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Tags: Computer science, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

Intel FPGA SDK for OpenCL

Intel Corporation

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Tags: Computer science, FPGA, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Shaohuai Shi, Xiaowen Chu

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Tags: Algorithms, Benchmarking, Caffe, Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Package, Performance, TensorFlow, Tesla P40, Torch

November 26, 2017 by hgpu

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

Maxence Reberol, Bruno Levy

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Tags: Computer science, nVidia, nVidia GeForce GTX 1080, OpenGL, Package, Traingular meshes

November 26, 2017 by hgpu

GPU Pro 7: Advanced Rendering

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, nVidia, OpenGL, Package, Rendering, Visualization

November 26, 2017 by hgpu

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Marcio M. Pereira, Rafael C. F. Sousa, Guido Araujo

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Tags: ARM, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, LLVM, nVidia, OpenCL, OpenMP, Package, Tesla K40

November 21, 2017 by hgpu

Hydra: a C++11 framework for data analysis in massively parallel platforms

A. A. Alves Junior, M. D. Sokoloff

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Tags: Computational Physics, Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Tesla K40

November 16, 2017 by hgpu

Accelerating HPC codes on Intel(R) Omni-Path Architecture networks: From particle physics to Machine Learning

Peter Boyle, Michael Chuvelev, Guido Cossu, Christopher Kelly, Christoph Lehner, Lawrence Meadows

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Tags: Benchmarking, Computer science, Intel Xeon Phi, Machine learning, MPI, OpenMP, Package, Performance, Physics

November 16, 2017 by hgpu

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Wim Vanderbauwhede, Gavin Davidson

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Tags: Compilers, Computer science, Fortran, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Package

November 16, 2017 by hgpu

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Leiming Yu, Fanny Nina-Paravecino, David Kaeli, Qianqian Fang

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Tags: Algorithms, AMD R9 Nano, AMD Radeon RX 480, ATI, Computational Physics, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 590, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan X, OpenCL, Package, Physics

November 12, 2017 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Packages

Intra-node Memory Safe GPU Co-Scheduling

On algorithmic reductions in task-parallel programming models

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Intel FPGA SDK for OpenCL

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

GPU Pro 7: Advanced Rendering

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Hydra: a C++11 framework for data analysis in massively parallel platforms

Accelerating HPC codes on Intel(R) Omni-Path Architecture networks: From particle physics to Machine Learning

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

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Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

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AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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