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Massive Exploration of Neural Machine Translation Architectures

Denny Britz, Anna Goldie, Thang Luong, Quoc Le

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Tags: Computer science, Deep learning, Neural networks, NLP, nVidia, Package, Python, TensorFlow, Tesla K40

March 14, 2017 by hgpu

Model-independent partial wave analysis using a massively-parallel fitting framework

Liang Sun, Rafael Aoude, Alberto Correa Dos Reis, Michael David Sokoloff

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Tags: Algorithms, CUDA, High Energy Physics - Experiment, nVidia, OpenMP, Package, Physics, Tesla K40

March 14, 2017 by hgpu

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

Andrew J. Younge

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Tags: Cloud, Computer science, CUDA, Distributed computing, Molecular dynamics, nVidia, OpenCL, Tesla C2075, Tesla K20, Thesis, Virtualization

March 9, 2017 by hgpu

Optimizing Deep CNN-Based Queries over Video Streams at Scale

Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia

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Tags: Computer science, Computer vision, Databases, Deep learning, Machine learning, Neural networks, nVidia, nVidia DGX-1, Package, TensorFlow, Tesla P100

March 9, 2017 by hgpu

A Machine-Learning Framework for Design for Manufacturability

Aditya Balu, Sambit Ghadai, Gavin Young, Soumik Sarkar, Adarsh Krishnamurthy

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Tags: CNN, Computer science, Deep learning, Keras, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro K 2200

March 9, 2017 by hgpu

Decoupled Block-Wise ILU(k) Preconditioner on GPU

Bo Yang, Hui Liu, He Zhong, Zhangxin Chen

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Tags: Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla K20

March 9, 2017 by hgpu

Wireless Interference Identification with Convolutional Neural Networks

Malte Schmidt, Dimitri Block, Uwe Meier

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Tags: CNN, Deep learning, Keras, Neural networks, nVidia, nVidia GeForce GTX 960, Signal processing

March 5, 2017 by hgpu

Improving the Neural GPU Architecture for Algorithm Learning

Karlis Freivalds, Renars Liepins

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Tags: Algorithms, Artificial intelligence, Computer science, Deep learning, Memory model, nVidia, Package, Python, TensorFlow, Tesla K40

March 5, 2017 by hgpu

Performance and Portability of Accelerated Lattice Boltzmann Applications with OpenACC

E. Calore, A. Gabbana, J. Kraus, S. F. Schifano, R. Tripiccione

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Tags: AMD FirePro S9150, ATI, Benchmarking, CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, OpenACC, OpenCL, Performance, Tesla K80

March 5, 2017 by hgpu

Billion-scale similarity search with GPUs

Jeff Johnson, Matthijs Douze, Herve Jegou

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Tags: Computer science, CUDA, Data Structures and Algorithms, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, Package

March 5, 2017 by hgpu

Speckle Reduction with Trained Nonlinear Diffusion Filtering

Wensen Feng, Yunjin Chen

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Tags: CNN, Computer vision, Filtering, Image processing, Matlab, nVidia, nVidia GeForce GXT 780 Ti, Package, SAR

February 28, 2017 by hgpu

An Efficient Multiway Mergesort for GPU Architectures

Henri Casanova, John Iacono, Ben Karsin, Nodari Sitchinava, Volker Weichert

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 770, nVidia Quadro M 4000, Sorting, Tesla K40

February 28, 2017 by hgpu

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

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high performance computing on graphics processing units: hgpu.org

Massive Exploration of Neural Machine Translation Architectures

Model-independent partial wave analysis using a massively-parallel fitting framework

Optimizing Deep CNN-Based Queries over Video Streams at Scale

A Machine-Learning Framework for Design for Manufacturability

Decoupled Block-Wise ILU(k) Preconditioner on GPU

Wireless Interference Identification with Convolutional Neural Networks

Improving the Neural GPU Architecture for Algorithm Learning

Performance and Portability of Accelerated Lattice Boltzmann Applications with OpenACC

Billion-scale similarity search with GPUs

Speckle Reduction with Trained Nonlinear Diffusion Filtering

An Efficient Multiway Mergesort for GPU Architectures

Recent source codes

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

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