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Showing 15 open source projects for "speed"
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TreeFrog Framework
TreeFrog Framework, High-speed C++ MVC Framework for Web Applications
TreeFrog Framework is a high-speed and full-stack C++ framework for developing Web applications, which supports HTTP and WebSocket protocol. Web applications can run faster than that of scripting language because the server-side framework was written in C++/Qt. In application development, it provides an O/R mapping system and template systems on an MVC architecture, aims to achieve high productivity through the policy of convention over configuration. -
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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Yoga
Cross-platform layout engine which implements Flexbox
Build flexible layouts on any platform with a highly optimized open source layout engine designed with speed, size, and ease of use in mind. Yoga already powers widely used open source frameworks. It enables these frameworks to offer a simple and intuitive layout API that allows for engineers to collaborate more easily across platforms. Yoga has unlocked exciting features such as calculating layouts off of the main thread to help ensure smooth UI performance. -
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MegEngine
Easy-to-use deep learning framework with 3 key features
...You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. ... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes obligatory when running a model. Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. ... -
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V8 JavaScript Engine
The official mirror of the V8 Git repository
V8 is Google’s high-performance, open-source JavaScript and WebAssembly engine written in C++, powering Chrome, Node.js, and embedded in many environments. It implements ECMAScript and WebAssembly standards with optimizations for speed and resource efficiency. V8 is Google's open source JavaScript engine. V8 implements ECMAScript as specified in ECMA-262. V8 is written in C++ and is used in Google Chrome, the open source browser from Google. V8 can run standalone, or can be embedded into any C++ application. -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. -
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Caffe
A fast open framework for deep learning
Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. ... -
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TreeFrog Framework
High-speed C++ MVC Framework for Web Application
TreeFrog Framework is a high-speed C++ MVC framework for developing Web applications. -
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Native C++ .NET Framework
A C++ framework based on .NET
The concept of this C++ framework based on .NET is to speed up the development of native C++ projects for Windows for developers more familiar with .NET. This framework also allows people to easily port C# apps to C++, although not a like-for-like port. Please note that this framework does NOT require .NET to be installed. There is no dependency or linking to any part of .NET. This framework simply uses the same class names and function names as .NET. -
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Low-latency high speed hybrid framework-library for utilizing the IBM Cell processor SPE units (PS3, QS20) to carry out computational tasks. Provides some DSP tasks such as FFT and complex MAC. Thread-safe and easily extensible with new arithmetics tasks
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The Official Address Normalizer parses a mailing address into a set of potentially matching US Postal Service standardized addresses. The library is intended for real-time usage and emphasizes speed over completeness.
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Wia stands for "With Instructions Already". Wia is a framework for C++ providing wide range of functions available to speed up development of applications.
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A replacement library which aim in replacing the default AmigaOS "layers.library" to more efficently manage layers operations on modern AmigaOS operating systems. It comes with some advanced layers techniques to speed up operations....
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