high performance computing on graphics processing units: hgpu.org

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An efficient numerical method for solving the Boltzmann equation in multidimensions

Giacomo Dimarco, Raphael Loubere, Jacek Narski, Thomas Rey

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Tags: Algorithms, Boltzmann equation, cfd, CUDA, Fluid dynamics, Mathematics, MPI, Numerical Analysis, nVidia, OpenMP, Physics

September 13, 2016 by hgpu

Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

Olivier Beaumont, Terry Cojean, Lionel Eyraud-Dubois, Abdou Guermouche, Suraj Kumar

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40

September 13, 2016 by hgpu

A New Architecture for Optimization Modeling Frameworks

Matt Wytock, Steven Diamond, Felix Heide, Stephen Boyd

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Tags: Algorithms, CUDA, Deep learning, Linear Algebra, Mathematics, nVidia, nVidia GeForce GTX Titan X, Package, Python

September 13, 2016 by hgpu

GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays

Muaaz Awan, Fahad Saeed

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Tags: Algorithms, big data, Computer science, CUDA, nVidia, Package, Sorting, Tesla K40

September 10, 2016 by hgpu

System Design Principles for Heterogeneous Resource Management and Scheduling in Accelerator-Based Systems

Dipanjan Sengupta

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Tags: Algorithms, Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro 2000, nVidia Quadro 4000, Task scheduling, Tesla C2050, Tesla C2070, Tesla K20, Thesis

September 10, 2016 by hgpu

3D Object Recognition with Convolutional Neural Networks

Alberto Garcia-Garcia

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Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GT 730, nVidia GeForce GTX Titan X, Tesla K40, Thesis

September 10, 2016 by hgpu

OpenSBLI: A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures

Christian T. Jacobs, Satya P. Jammy, Neil D. Sandham

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Tags: cfd, Code generation, Computer science, CUDA, Finite difference, Fluid dynamics, Mathematical Software, MPI, nVidia, OpenCL, Tesla K40

September 10, 2016 by hgpu

Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong

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Tags: Caffe, Computer science, CUDA, Deep learning, DSP, FPGA, Neural networks, nVidia, Tesla K40

September 8, 2016 by hgpu

A Lightweight Approach to Performance Portability with targetDP

Alan Gray, Kevin Stratford

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, performance portability, QCD, Tesla K20, Tesla K40

September 8, 2016 by hgpu

A Non-linear GPU Thread Map for Triangular Domains

Cristobal A. Navarro, Benjamin Bustos, Nancy Hitschfeld

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 765 M, Performance, Tesla K40

September 8, 2016 by hgpu

OpenCL/CUDA algorithms for parallel decoding of any irregular LDPC code using GPU

Jan Broulim, Alexander Ayriyan, Vjaceslav Georgiev

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Tags: Algorithms, Computer science, CUDA, Error recovery, nVidia, OpenCL, Tesla K40, Tutorial

September 8, 2016 by hgpu

Parallel Tree Traversal for Nearest Neighbor Query on the GPU

Moohyeon Nam, Jinwoong Kim, Beomseok Nam

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Tags: Algorithms, Biology, Computational biology, Computer science, CUDA, Information Retrieval, Nearest neighbour, nVidia, Tesla K40

September 5, 2016 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

An efficient numerical method for solving the Boltzmann equation in multidimensions

Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

A New Architecture for Optimization Modeling Frameworks

GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays

3D Object Recognition with Convolutional Neural Networks

OpenSBLI: A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures

Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

A Lightweight Approach to Performance Portability with targetDP

A Non-linear GPU Thread Map for Triangular Domains

OpenCL/CUDA algorithms for parallel decoding of any irregular LDPC code using GPU

Parallel Tree Traversal for Nearest Neighbor Query on the GPU

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