librte-baseband-acc100-22

Data Plane Development Kit (librte-baseband-acc100 runtime library)

DPDK is a set of libraries for fast packet processing. Applications run in user-space and communicate directly with dedicated network interfaces.

libghc-ogma-language-jsonspec-prof

Ogma: Runtime Monitor translator: JSON Frontend; profiling libraries

Ogma is a tool to facilitate the integration of safe runtime monitors into other systems. Ogma extends <https://github.com/Copilot-Language/copilot Copilot>, a high-level runtime verification framework that generates hard real-time C99 code.

postgresql-14-ogr-fdw

PostgreSQL foreign data wrapper for OGR

OGR is the vector half of the GDAL spatial data access library. It allows access to a large number of GIS data formats using a simple C API for data reading and writing. Since OGR exposes a simple table structure and PostgreSQL foreign data wrappers allow access to table structures, the fit seems pretty perfect.

qml-module-qzxing

QZXing QML/QtQuick module

Qt wrapper for the ZXing 1D/2D barcode image decoder.

libqt6nfc6

Qt 6 Connectivity NFC library

Qt is a cross-platform C++ application framework. Qt's primary feature is its rich set of widgets that provide standard GUI functionality.

libstopt4

library for stochastic optimization problems (shared library)

The STochastic OPTimization library (StOpt) aims at providing tools in C++ for solving some stochastic optimization problems encountered in finance or in the industry. Different methods are available: - dynamic programming methods based on Monte Carlo with regressions (global, local, kernel and sparse regressors), for underlying states following some uncontrolled Stochastic Differential Equations; - dynamic programming with a representation of uncertainties with a tree: transition problems are here solved by some discretizations of the commands, resolution of LP with cut representation of the Bellman values; - Semi-Lagrangian methods for Hamilton Jacobi Bellman general equations for underlying states following some controlled Stochastic Differential Equations; - Stochastic Dual Dynamic Programming methods to deal with stochastic stock management problems in high dimension. Uncertainties can be given by Monte Carlo and can be represented by a state with a finite number of values (tree); - Some branching nesting methods to solve very high dimensional non linear PDEs and some appearing in HJB problems. Besides some methods are provided to solve by Monte Carlo some problems where the underlying stochastic state is controlled. For each method, a framework is provided to optimize the problem and then simulate it out of the sample using the optimal commands previously computed. Parallelization methods based on OpenMP and MPI are provided in this framework permitting to solve high dimensional problems on clusters. The library should be flexible enough to be used at different levels depending on the user's willingness.