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GPU-based Acceleration of Deep Convolutional Neural Networks on Mobile Platforms

Seyyed Salar Latifi Oskouei, Hossein Golestani, Mohamad Kachuee, Matin Hashemi, Hoda Mohammadzade, Soheil Ghiasi

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Tags: ARM, Computer science, Computer vision, Deep learning, Machine learning, Neural networks, RenderScript

November 25, 2015 by hgpu

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

Liang-Chieh Chen

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Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 650 M, OpenCV, Tesla K40, Thesis

November 24, 2015 by hgpu

Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations

Garrick Orchard, Jacob G. Martin, R. Jacob Vogelstein, Ralph Etienne-Cummings

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Tags: Computer science, Computer vision, FPGA

November 13, 2015 by hgpu

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

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Vincenzo Lomonaco

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Pattern recognition, Tesla C2075, Thesis

November 8, 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

Self-Adapting Parallel Framework for Long-Term Object Tracking

Salim Mohammed Ali

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Tags: AMD Radeon HD 8970 M, ATI, Computer science, Computer vision, nVidia, nVidia GeForce GTX 580, OpenCL, Thesis

October 18, 2015 by hgpu

Optimal Piecewise Linear Function Approximation for GPU-based Applications

Daniel Berjon, Guillermo Gallego, Carlos Cuevas, Francisco Moran, Narciso Garcia

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Tags: Computer science, Computer vision, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 580

October 13, 2015 by hgpu

Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion

Wensen Feng, Yunjin Chen

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Tags: CNN, Computer science, Computer vision, Microscopy, nVidia, nVidia GeForce GTX 780 Ti, Signal denoising

October 13, 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

Fast Exact Bayesian Inference for High-Dimensional Models

Joao Filipe Ferreira, Pablo Lanillos, Jorge Dias

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Tags: Bayesian, Computer science, Computer vision, nVidia, nVidia GeForce GTX 780, OpenCL, Robotics

September 26, 2015 by hgpu

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Vlad Olaru, Mihai Florea, Cristian Sminchisescu

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Tags: Algorithms, Computer science, Computer vision, CUDA, Matlab, nVidia, nVidia GeForce GTX Titan Black, Package, Tesla K40

September 24, 2015 by hgpu

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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