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TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

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Tags: Computer science, Computer vision, CUDA, Deep learning, Heterogeneous systems, Information Retrieval, Machine learning, Neural networks, nVidia, Package, Speech recognition

November 11, 2015 by hgpu

Accelerating Twisted Mass LQCD with QPhiX

Mario Schrock, Silvano Simula, Alexei Strelchenko

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Tags: High Energy Physics - Lattice, Intel Xeon Phi, Package, Physics, QCD

November 4, 2015 by hgpu

Structural Agnostic SpMV: Adapting CSR-Adaptive for Irregular Matrices

Mayank Daga, Joseph L. Greathouse

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Tags: Algorithms, AMD FirePro W9100, APU, ATI, Computer science, Linear Algebra, OpenCL, Package, Sparse matrix

November 3, 2015 by hgpu

CLOP: A Multi-stage Compiler to Seamlessly Embed Heterogeneous Code

Dmitri Makarov, Matthias Hauswirth

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Tags: Compilers, Computer science, OpenCL, Package

October 29, 2015 by hgpu

ZNN – A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

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Tags: CNN, Computer science, Computer vision, Deep learning, FFT, Intel Xeon Phi, Machine learning, Package

October 25, 2015 by hgpu

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K40

October 22, 2015 by hgpu

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

Changbo Chen, Xiaohui Chen, Abdoul-Kader Keita, Marc Moreno Maza, Ning Xie

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Tags: Code generation, Computer science, CUDA, nVidia, Package

October 18, 2015 by hgpu

Sapporo2: A versatile direct N-body library

Jeroen Bedorf, Evghenii Gaburov, Simon Portegies Zwart

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Tags: Astrophysics, ATI, ATI Radeon HD 7970, CUDA, Instrumentation and Methods for Astrophysics, Mathematical Software, N-body simulation, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Tesla K20

October 16, 2015 by hgpu

Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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Tags: Benchmarking, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 560, Package, Speech recognition

October 8, 2015 by hgpu

GPU-Based Computation of 2D Least Median of Squares with Applications to Fast and Robust Line Detection

Gil Shapira, Tal Hassner

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 720, Package

October 8, 2015 by hgpu

Kinematic Modelling of Disc Galaxies using Graphics Processing Units

Georgios Bekiaris, Karl Glazebrook, Christopher J. Fluke, Roberto Abraham

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Tags: Algorithms, Astrophysics, CUDA, nVidia, Package, Tesla C2070, Tesla K40

October 8, 2015 by hgpu

MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing

Azzam Haidar, Stanimire Tomov, Piotr Luszczek, Jack Dongarra

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia Jetson TK1, Package

October 6, 2015 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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