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Protocol Buffers (Protobuf) is a free and open-source cross-platform data format used to serialize structured data. It is useful in developing programs that communicate with each other over a network or for storing data.
The high-level design focuses on speed and security, making it suitable for network as well as inter-process communication. Cap'n Proto was created by the former maintainer of Google's popular Protocol Buffers framework (Kenton Varda) and was designed to avoid some of its perceived shortcomings.
^ ASN.1 has X.681 (Information Object System), X.682 (Constraints), and X.683 (Parameterization) that allow for the precise specification of open types where the types of values can be identified by integers, by OIDs, etc. OIDs are a standard format for globally unique identifiers, as well as a standard notation ("absolute reference") for ...
This is a list of data types of the Standard Libraries as defined in the ECMA-335 standard. Implementations of the Common Language Infrastructure must define the types of the standard in their respective standard libraries. The standard encourages implementers to extend or to modify the types specified in the standard to provide additional ...
A lower data-centric publish-subscribe (DCPS) level that is targeted towards the efficient delivery of the proper information to the proper recipients. An optional higher data local reconstruction layer (DLRL), which allows for a simple integration of DDS into the application layer. Other related standards followed the initial core document.
Hardware and software for machine learning or neural networks tend to use half precision: such applications usually do a large amount of calculation, but don't require a high level of precision. Due to hardware typically not supporting 16-bit half-precision floats, neural networks often use the bfloat16 format, which is the single precision ...
The Library of Efficient Data types and Algorithms (LEDA) is a proprietarily-licensed software library providing C++ implementations of a broad variety of algorithms for graph theory and computational geometry. [1] It was originally developed by the Max Planck Institute for Informatics Saarbrücken. [2]
software.intel.com /content /www /us /en /develop /tools /data-analytics-acceleration-library.html oneAPI Data Analytics Library (oneDAL; formerly Intel Data Analytics Acceleration Library or Intel DAAL), is a library of optimized algorithmic building blocks for data analysis stages most commonly associated with solving Big Data problems.