PadicoTM is composed of a core which provides a high-performance framework for networking and multi-threading, and services plugged into the core. High-performance communications and threads are obtained thanks to Marcel and Madeleine, provided by the PM2 software suite. The PadicoTM core aims at making the different services running at the same time run in a cooperative way rather than competitive.

Small library with routines to synchronize clocks over several nodes with MPI.

NewMadeleine is the fourth incarnation of the Madeleine communication library. The new architecture aims at enabling the use of a much wider range of communication flow optimization techniques. Its design is entirely modular: drivers and optimization strategies are dynamically loadable software components, allowing experimentations with multiple approaches or on multiple issues with regard to processing communication flows. The optimizing scheduler SchedOpt targets applications with irregular, multi-flow communication schemes such as found in the increasingly common application conglomerates made of multiple programming environments and coupled pieces of code, for instance. SchedOpt itself is easily extensible through the concepts of optimization strategies (what to optimize for, what the optimization goal is) expressed in terms of tactics (how to optimize to reach the optimization goal). Tactics themselves are made of basic communication flows operations such as packet merging or reordering. The communication library is fully multi-threaded through its close integration with PIOMan. It manages concurrent communication operations from multiple libraries and from multiple threads. Its MPI implementation Mad-MPI fully supports the MPI_THREAD_MULTIPLE multi-threading level.

NewMadeleine is the fourth incarnation of the Madeleine communication library. The new architecture aims at enabling the use of a much wider range of communication flow optimization techniques. Its design is entirely modular: drivers and optimization strategies are dynamically loadable software components, allowing experimentations with multiple approaches or on multiple issues with regard to processing communication flows. The optimizing scheduler SchedOpt targets applications with irregular, multi-flow communication schemes such as found in the increasingly common application conglomerates made of multiple programming environments and coupled pieces of code, for instance. SchedOpt itself is easily extensible through the concepts of optimization strategies (what to optimize for, what the optimization goal is) expressed in terms of tactics (how to optimize to reach the optimization goal). Tactics themselves are made of basic communication flows operations such as packet merging or reordering. The communication library is fully multi-threaded through its close integration with PIOMan. It manages concurrent communication operations from multiple libraries and from multiple threads. Its MPI implementation Mad-MPI fully supports the MPI_THREAD_MULTIPLE multi-threading level.

OpenBLAS is a Basic Linear Algebra Subprograms (BLAS) library forked from the GotoBLAS2-1.13 BSD version.

Test mumps

MUMPS (MUltifrontal Massively Parallel sparse direct Solver) solves a sparse system of linear equations A x = b using Gaussian elimination.

MUMPS (MUltifrontal Massively Parallel sparse direct Solver) solves a sparse system of linear equations A x = b using Gaussian elimination.

Test mumps

Likwid is a simple to install and use toolsuite of command line applications and a library for performance oriented programmers. It works for Intel, AMD, ARMv8 and POWER9 processors on the Linux operating system. There is additional support for Nvidia GPUs. There is support for ARMv7 and POWER8 but there is currently no test machine in our hands to test them properly. Note that in this recipe we compile the package with ACCESSMODE=perf_event because we lack the root privileges on HPC platforms. One of the implications is that thermic measures are disabled. See the Wiki on the home page of the package for more details.

gcvb (generate compute validate benchmark) is a Python 3 module aiming at facilitating non-regression, validation and benchmarking of simulation codes. gcvb is not a complete tool of continuous integration (CI). It is rather a component of the testing part of a CI workflow. It can compare the different metrics of your computation with references that can be a file, depends of the 'configuration' or are absolute. This is the fork of Marek Felšöci.

One of the most advanced WSGI utility modules. It includes a powerful debugger, full-featured request and response objects, HTTP utilities to handle entity tags, cache control headers, HTTP dates, cookie handling, file uploads, a powerful URL routing system and a bunch of community-contributed addon modules.

gcvb (generate compute validate benchmark) is a Python 3 module aiming at facilitating non-regression, validation and benchmarking of simulation codes. gcvb is not a complete tool of continuous integration (CI). It is rather a component of the testing part of a CI workflow. It can compare the different metrics of your computation with references that can be a file, depends of the 'configuration' or are absolute. This is a minimal version without the dashboard functionality. This is the fork of Marek Felšöci.

Python client library for visual regression testing with Percy (https://percy.io).

Example of a Dash library that uses Flow Types.

Vanilla HTML components for Dash.

Deferring loading of JS files until after React loads.

gcvb (generate compute validate benchmark) is a Python 3 module aiming at facilitating non-regression, validation and benchmarking of simulation codes. gcvb is not a complete tool of continuous integration (CI). It is rather a component of the testing part of a CI workflow. It can compare the different metrics of your computation with references that can be a file, depends of the 'configuration' or are absolute.

Dash table.

gcvb (generate compute validate benchmark) is a Python 3 module aiming at facilitating non-regression, validation and benchmarking of simulation codes. gcvb is not a complete tool of continuous integration (CI). It is rather a component of the testing part of a CI workflow. It can compare the different metrics of your computation with references that can be a file, depends of the 'configuration' or are absolute. This is a minimal version without the dashboard functionality.

This package provides a dash component for specifying raw HTML.

This package provides a Python framework for building reactive web-apps. Developed by Plotly.

Core component suite for Dash.

Flask is a micro web framework based on the Werkzeug toolkit and Jinja2 template engine. It is called a micro framework because it does not presume or force a developer to use a particular tool or library.