Search Results for "network architecture"
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Showing 8 open source projects for "network architecture"
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1
oneDNN
oneAPI Deep Neural Network Library (oneDNN)
This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the following architectures: Arm* 64-bit Architecture (AArch64), NVIDIA* GPU, OpenPOWER* Power ISA (PPC64), IBMz* (s390x), and RISC-V. oneDNN is intended for deep learning applications and framework developers interested in improving application performance on Intel CPUs and GPUs. ... -
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COCOON
Confidential Compute Open Network, Decentralized AI Inference on TON
COCOON is a privacy-aware desktop client framework designed by the developers of Telegram to provide a modern, secure, and extensible environment for building messaging and communication applications. At its core, it combines native desktop performance with web-like flexibility, packing a renderer, UI components, and plugin architecture that allows developers to craft rich experiences similar to those found in native apps. Cocoon’s architecture prioritizes privacy and security, making it... -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
...With new NVIDIA Ampere Architecture GPUs, TensorRT also leverages sparse tensor cores providing an additional performance boost. -
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UCCL
UCCL is an efficient communication library for GPUs
...It supports a variety of communication patterns including collective operations such as all-reduce as well as peer-to-peer transfers that are commonly used in modern machine learning architectures. UCCL is designed to work with heterogeneous hardware environments, allowing GPUs from different vendors and network interfaces to communicate efficiently without vendor lock-in. The system also supports specialized workloads such as reinforcement learning weight transfers, key-value cache sharing, and expert parallelism for mixture-of-experts models. Its architecture emphasizes flexibility and extensibility so that developers can implement custom communication protocols tailored to specific machine learning workloads. -
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5
PowerInfer
High-speed Large Language Model Serving for Local Deployment
PowerInfer is a high-performance inference engine designed to run large language models efficiently on personal computers equipped with consumer-grade GPUs. The project focuses on improving the performance of local AI inference by optimizing how neural network computations are distributed between CPU and GPU resources. Its architecture exploits the observation that only a subset of neurons in large models are frequently activated, allowing the system to preload frequently used neurons into GPU memory while processing less common activations on the CPU. This hybrid execution strategy significantly reduces memory bottlenecks and improves overall inference speed. ... -
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Convolutional Recurrent Neural Network
Convolutional Recurrent Neural Network (CRNN) for image-based sequence
Convolutional Recurrent Neural Network provides an implementation of the Convolutional Recurrent Neural Network (CRNN) architecture, a deep learning model designed for image-based sequence recognition tasks such as optical character recognition and scene text recognition. The architecture combines convolutional neural networks for extracting visual features from images with recurrent neural networks that model sequential dependencies in the extracted features. ... -
7
NARX simulator with neural networks
A simulator for NARX ( Nonlinear AutoRegressive with eXogenous inputs)
This projects aims at creating a simulator for the NARX (Nonlinear AutoRegressive with eXogenous inputs ) architecture with neural networks. The system can fallback to MLP ( multi layer perceptron ), TDNN ( time delay neural network ), BPTT ( backpropagation through time ) and a full NARX architecture. The system is intended to be used as a time series forecaster for educational purposes. This projects is my personal master thesis developed at the Master of Artificial Intelligence at Universitat Polytecnica de Catalunya, Barcelona The project presents artificial generated data but also real data tests from temperature, weather, economy. ... -
8
nunn
This is an implementation of a machine learning library in C++17
nunn is a collection of ML algorithms and related examples written in modern C++17.
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