Neural networks | Page 41

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Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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

October 22, 2014 by hgpu

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

Xiangang Li, Xihong Wu

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Tags: Computer science, Evolutionary Computations, Neural and Evolutionary Computing, Neural networks, Speech recognition

October 18, 2014 by hgpu

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

Di Wu, Ling Shao

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Tags: CNN, Computer science, CUDA, Neural networks, nVidia, Package, Python, Rendering

October 4, 2014 by hgpu

GPU Implementation of a Deep Learning Network for Financial Prediction

Robin Kumar, Amandeep Kaur Cheema

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Tags: Artificial intelligence, Finance, Java, Machine learning, Neural networks, OpenCL

September 17, 2014 by hgpu

Caffe: Convolutional Architecture for Fast Feature Embedding

Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell

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Tags: Cloud, Computer science, CUDA, Neural networks, nVidia, Package, Pattern recognition, Python

August 23, 2014 by hgpu

Fast Semantic Segmentation of RGB-D Scenes with GPU-Accelerated Deep Neural Networks

Nico Hoft, Hannes Schulz, Sven Behnke

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

August 9, 2014 by hgpu

Accelerated Matrix Element Method with Parallel Computing

Doug Schouten, Adam DeAbreu, Bernd Stelzer

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Tags: AMD Radeon R9 290, ATI, Computational Complexity, Computational Physics, Monte Carlo integration, Neural networks, OpenCL, Physics, Probability

August 2, 2014 by hgpu

Discriminative Convolutional Sum-Product Networks on GPU

Tobias Hartmann

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Tags: Algorithms, Benchmarking, Computer science, Computer vision, CUDA, Neural networks, nVidia, Tesla K20, Thesis

August 1, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Hasse Lovgren

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Tags: ATI, ATI Radeon HD 5870, Computer science, Mathematics, Neural networks, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Tesla C1060, Thesis

July 9, 2014 by hgpu

Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition

Andrew L. Maas, Awni Y. Hannun, Christopher T. Lengerich, Peng Qi, Daniel Jurafsky, Andrew Y. Ng

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Tags: Computer science, Machine learning, Neural and Evolutionary Computing, Neural networks, Speech recognition

July 1, 2014 by hgpu

Feature Generation for Quantification of Visual Similarity

Tianning Steven Han

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Tags: Algorithms, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla K20, Thesis

June 23, 2014 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

GPU Implementation of a Deep Learning Network for Financial Prediction

Fast Semantic Segmentation of RGB-D Scenes with GPU-Accelerated Deep Neural Networks

Accelerated Matrix Element Method with Parallel Computing

Discriminative Convolutional Sum-Product Networks on GPU

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition

Feature Generation for Quantification of Visual Similarity

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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