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OpenMP as a High-Level Specification Language for Parallelism And its use in Evaluating Parallel Programming Systems

Max Grossman, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, LLVM, nVidia, OpenMP, Package

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

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

QSL Squasher: A Fast Quasi-Separatrix Layer Map Calculator

Svetlin Tassev, Antonia Savcheva

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Tags: AMD FirePro W8100, Astrophysics, ATI, OpenCL, Package, Solar and Stellar Astrophysics

September 8, 2016 by hgpu

Matrix Computations and Optimization in Apache Spark

Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Sparks, Aaron Staple, Matei Zaharia

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, Package, Scala, Spark, Tesla M2050

September 3, 2016 by hgpu

Fast 4D Sheared Filtering for Interactive Rendering of Distribution Effects

Ling-Qi Yan, Soham Uday Mehta, Ravi Ramamoorthi, Fredo Durand

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX Titan, Package, Raytracing, Rendering

September 3, 2016 by hgpu

DeepPy: Pythonic deep learning

Anders Boesen Lindbo Larsen

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Python

September 3, 2016 by hgpu

SafeGPU: Contract- and Library-Based GPGPU for Object-Oriented Languages

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package

August 31, 2016 by hgpu

A Performance Model and Optimization Strategies for Automatic GPU Code Generation of PDE Systems Described by a Domain-Specific Language

Yue Hu

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Tags: Code generation, Computer science, CUDA, DSL, Fluid dynamics, Intel Xeon Phi, nVidia, OpenCL, Package, PDEs, PTX, Stencil computation, Tesla K20, Thesis

August 31, 2016 by hgpu

Benchmarking State-of-the-Art Deep Learning Software Tools

Shaohuai Shi, Qiang Wang, Pengfei Xu, Xiaowen Chu

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Tags: Benchmarking, CNN, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, Package, RNN, Tesla K80

August 28, 2016 by hgpu

Fast Multidimensional Image Processing with OpenCL

Daniel Oliveira Dantas, Helton Danilo Passos Leal, Davy Oliveira Barros Sousa

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Tags: AMD Radeon R9 270X, ATI, CUDA, GLSL, Image processing, OpenCL, Package

August 23, 2016 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

OpenMP as a High-Level Specification Language for Parallelism And its use in Evaluating Parallel Programming Systems

A New Architecture for Optimization Modeling Frameworks

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

A Lightweight Approach to Performance Portability with targetDP

QSL Squasher: A Fast Quasi-Separatrix Layer Map Calculator

Matrix Computations and Optimization in Apache Spark

Fast 4D Sheared Filtering for Interactive Rendering of Distribution Effects

DeepPy: Pythonic deep learning

SafeGPU: Contract- and Library-Based GPGPU for Object-Oriented Languages

A Performance Model and Optimization Strategies for Automatic GPU Code Generation of PDE Systems Described by a Domain-Specific Language

Benchmarking State-of-the-Art Deep Learning Software Tools

Fast Multidimensional Image Processing with OpenCL

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HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

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Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

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