high performance computing on graphics processing units: hgpu.org

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Gunrock: GPU Graph Analytics

Yangzihao Wang, Yuechao Pan, Andrew Davidson, Yuduo Wu, Carl Yang, Leyuan Wang, Muhammad Osama, Chenshan Yuan, Weitang Liu, Andy T. Riffel, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 8, 2017 by hgpu

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

Daniel George, E. A. Huerta

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Tags: Algorithms, Artificial intelligence, Astrophysics, CUDA, Deep learning, Filtering, Gravitation, Gravitational waves, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, Physics, Signal processing, Tesla K40, Tesla P100

January 4, 2017 by hgpu

Massively Parallel Computation of Accurate Densities for N-body Dark Matter Simulations using the Phase-Space-Element Method

Ralf Kaehler

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Tags: Astrophysics, Computational Physics, CUDA, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Package, Physics, Tesla K80, Tessellation

January 4, 2017 by hgpu

An initial performance review of software components for a heterogeneous computing platform

Ivan Svogor

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Tags: ATI, ATI Radeon HD 7750, Computer science, Energy-efficient computing, FPGA, Heterogeneous systems, OpenCL, Performance, Robotics

January 4, 2017 by hgpu

Synthesizing Benchmarks for Predictive Modeling

Chris Cummins, Pavlos Petoumenos, Zheng Wang, Hugh Leather

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Compilers, Computer science, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan, OpenCL, Package

December 31, 2016 by hgpu

Automatic OpenCL Task Adaptation for Heterogeneous Architectures

Pierre Huchant, Marie-Christine Counilh, Denis Barthou

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Tags: Compilers, Computer science, Heterogeneous systems, nVidia, nVidia Quadro K5000, OpenCL, Tesla K20, Tesla M2075

December 31, 2016 by hgpu

Android Malware Classification Using Parallelized Machine Learning Methods

Lifan Xu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, OpenMP, Security, Tesla C2050, Thesis

December 31, 2016 by hgpu

Parallel Digital Predistortion Design on Mobile GPU and Embedded Multicore CPU for Mobile Transmitters

Kaipeng Li, Amanullah Ghazi, Chance Tarver, Jani Boutellier, Mahmoud Abdelaziz, Lauri Anttila, Markku Juntti, Mikko Valkama, Joseph R. Cavallaro

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Tags: ARM, CUDA, nVidia, nVidia Jetson TK1, nVidia Tegra TX1, Signal processing, SoC

December 31, 2016 by hgpu

dOpenCL – Evaluation of an API-Forwarding Implementation

Karsten Tausche, Max Plauth, Andreas Polze

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Tags: Computer science, Distributed computing, MPI, OpenCL, Package, Virtualization

December 31, 2016 by hgpu

Batched Shift Reduce Parsing with Lists of Vectors on CUDA

Andrew Drozdov

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, nVidia GeForce GTX Titan Black, Package, Torch

December 26, 2016 by hgpu

Function Call Re-Vectorization

Rubens E. A. Moreira, Sylvain Collange, Fernando Magno Quintao Pereira

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Package, String matching

December 26, 2016 by hgpu

Language Modeling with Gated Convolutional Networks

Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, Performance, Tesla M40, Torch

December 26, 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

Programming

Gunrock: GPU Graph Analytics

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

Massively Parallel Computation of Accurate Densities for N-body Dark Matter Simulations using the Phase-Space-Element Method

An initial performance review of software components for a heterogeneous computing platform

Synthesizing Benchmarks for Predictive Modeling

Automatic OpenCL Task Adaptation for Heterogeneous Architectures

Android Malware Classification Using Parallelized Machine Learning Methods

Parallel Digital Predistortion Design on Mobile GPU and Embedded Multicore CPU for Mobile Transmitters

dOpenCL – Evaluation of an API-Forwarding Implementation

Batched Shift Reduce Parsing with Lists of Vectors on CUDA

Function Call Re-Vectorization

Language Modeling with Gated Convolutional Networks

Recent source codes

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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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