Search Results for "algorithms framework"
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Showing 50 open source projects for "algorithms framework"
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CPlusPlusThings
Collection of various C++ code samples, utilities, patterns
CPlusPlusThings is a repository collecting various C++ code samples, utilities, patterns, and small example projects. It is less a polished product and more a learning/reference collection of snippets and usages of C++ idioms, data structures, algorithms, utilities, and perhaps tricks or meta-programming exercises. (No prominent README or detailed docs were available from my quick search.) Example implementations of data structures and algorithms. Organized as a learning repository (rather than a production framework). Encourages reuse and adaptation by developers as a reference. ... -
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OpenSpiel
Environments and algorithms for research in general reinforcement
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and sequential, strictly turn-taking and simultaneous-move, perfect and imperfect information games, as well as traditional multiagent environments such as (partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel also includes tools to... -
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QPanda 2
QPanda 2 is an open source quantum computing framework
QPanda2 is an open source quantum computing framework developed by Origin Quantum, which can be used to build, run and optimize quantum algorithms. QPanda2 is the basic library of a series of software developed by Origin Quantum, which provides core components for QRunes, Qurator and quantum computing services. -
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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TensorFlow
TensorFlow is an open source library for machine learning
...TensorFlow expresses its computations as dataflow graphs, with each node in the graph representing an operation. Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. Tensorflow can also be used for research and production with TensorFlow Extended. -
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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and 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... -
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XGBoost
Scalable and Flexible Gradient Boosting
...It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
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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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Instigate Application Framework
Software libraries for effective development of desktop applications.
Instigate Application Framework provides software development methodology supported by development tools and libraries for cost effective development of high quality desktop applications with focus on CAD applications. Main benefit of Instigate Application Framework is genericity and non-intrusiveness. Framework does not enforce its own database upon application developer, but provides API to register user database and algorithms. -
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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CloudI is an open-source private cloud computing framework for efficient, secure, and internal data processing. CloudI provides scaling for previously unscalable source code with efficient fault-tolerant execution of ATS, C/C++, Erlang/Elixir, Go, Haskell, Java, JavaScript/node.js, OCaml, Perl, PHP, Python, Ruby, or Rust services. The bare essentials for efficient fault-tolerant processing on a cloud!
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FuzzBench
FuzzBench - Fuzzer benchmarking as a service
FuzzBench is a large-scale, open research platform developed by Google to evaluate and benchmark fuzzers — automated software testing tools that detect vulnerabilities through randomized input generation. It provides a standardized, reproducible environment for comparing the performance and effectiveness of different fuzzing algorithms on real-world software targets. FuzzBench integrates with the OSS-Fuzz infrastructure, allowing it to run experiments on authentic open source projects and... -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across multiple domains. Flashlight can be broken down into several components as described above. Each component can be incrementally built by specifying the correct build options. ... -
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LTI-Lib is an object oriented computer vision library written in C++ for Windows/MS-VC++ and Linux/gcc. It provides lots of functionality to solve mathematical problems, many image processing algorithms, some classification tools and much more...
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SSHTOOLS
Java SSH API
This project now hosts the third-generation of Java SSH API, Maverick Synergy. This API builds on the Maverick Legacy commercial APIs and delivers a new API in a unified client/server framework. This API is available to the community under the LGPL open source license. This update includes ed25519 support, support for the new OpenSSH private key file format and stronger key exchange algorithms. The project continues to host both the original API and legacy applications created around it, however, these are now considered deprecated and we do not recommend their use in anyway. -
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FastFlow: programming multi-core
Pattern-based multi/many-core parallel programming framework
FastFlow is a C/C++ programming framework supporting the development of pattern-based parallel programs on multi/many-core, GPUs and distributed platforms. FastFlow run-time is built upon non-blocking threads and lock-free queues. Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on... -
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FUMOLA - Functional Mock-up Laboratory
An FMI-based co-simulation framework.
FUMOLA is a co-simulation framework specifically designed to support the features offered by the FMI specification. It provides a flexible platform that allows to configure and execute co-simulation setups in an easy way. FUMOLA is developed on top of the Ptolemy II framework (https://ptolemy.eecs.berkeley.edu) and the FMI++ library (http://fmipp.sourceforge.net). The online documentation of FUMOLA is available here: https://sourceforge.net/p/fumola/wiki/Home/ -
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CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.
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StochKit is an extensible stochastic simulation framework developed in C++ that aims to make stochastic simulation accessible to practicing biologists and chemists, while remaining open to extension via new stochastic and multiscale algorithms. StochKit is part of the StochSS project [http://www.stochss.org/], and we are relying on continued funding for sustained development. Please consider registering to show your support.
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vrecko
virtual environment framework
Vrecko is a component-based system capable of management and display of virtual worlds using various input and output devices. It is in development by HCI (Human-Computer Interaction) laboratory at Faculty of Informatics, Masaryk University, Czech Republic. -
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CLAW is a C++ Library providing various tools in different domains, like a Tweener framework, Bézier curves manipulation, a map with multiple value types, a binary search tree container implemented as an AVL and an implementation of the sockets as std::stream. The library also includes a set of classes to easily load and write png, jpeg, gif files and other image formats. Finally, a part of the library is devoted to artificial intelligence in games and includes a generic alpha-beta...
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HIPAcc
Heterogeneous Image Processing Acceleration (HIPACC) Framework
HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages. -
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dev-apf
Application Programming Framework
dev-apf is to make an application easy, fast, and cross-platform. This framework includes algorithms, net, rpc, db, logger, util, and common classes. You are more than welcome in any activity including bug reporting, or feed-back. Cheers, -
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MapReduce++ is a project for implementation of parallel algorithms. It has currently two C++ implementations of the MapReduce abstraction: the MapMP library (multiprocessors) and the MaPI framework (multicomputers).
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Simple Application Framework is a library aiming at providing a rich set of generic classes and functions enabling rapid development of robust and safe applications. The library is written in C++ and places emphasis on clean and extensible object-oriented design and efficient algorithms. It is intended as a replacement and extension of the Standard Template Library (STL) that would be closer to modern trends in IT represented by the Base Class Library in .NET or the Java Class Library.
