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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

Key Reconciliation with Low-Density Parity-Check Codes for Long-Distance Quantum Cryptography

Mario Milicevic, Chen Feng, Lei M. Zhang, P. Glenn Gulak

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Tags: CUDA, nVidia, nVidia GeForce GTX 1080, Parity-check codes, Physics, Quantum Physics, Security

February 28, 2017 by hgpu

Deep Voice: Real-time Neural Text-to-Speech

Sercan O. Arik, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

February 28, 2017 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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