libace-inet-ssl-7.1.2

ACE SSL-enabled Inet protocol library

This package provides an ACE addon library for clients (and possibly servers at some point) using Inet protocols which support SSL, such as HTTPS or FTPS.

python3-mariadb-connector

Enables Python programs to access MariaDB and MySQL database

MariaDB Connector/Python enables Python programs to access MariaDB and MySQL databases, using an API which is compliant with the Python DB API 2.0 (PEP-249). It is written in C and Python and uses MariaDB Connector/C client library for client server communication.

libecal-2.0-3

Client library for evolution calendars

Evolution is the integrated mail, calendar, task and address book distributed suite from Novell, Inc.

elpa-vterm

fully-fledged terminal emulator inside GNU Emacs based on libvterm - elisp

Emacs-libvterm (vterm) is fully-fledged terminal emulator inside GNU Emacs based on libvterm, a C library. As a result of using compiled code (instead of elisp), emacs-libvterm is fully capable, fast, and it can seamlessly handle large outputs.

emacs-libvterm

fully-fledged terminal emulator inside GNU Emacs based on libvterm - module

Emacs-libvterm (vterm) is fully-fledged terminal emulator inside GNU Emacs based on libvterm, a C library. As a result of using compiled code (instead of elisp), emacs-libvterm is fully capable, fast, and it can seamlessly handle large outputs.

libstopt5t64

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.