Get started with Damaris

To get started, have a look at the following pages: Instrumenting a Simulation and Data Description. These pages introduce the C and FORTRAN client side API and the XML configuration file to configure Damaris and describe the data being passed through to its server side processing plugins.

To access the Damaris source code, it is available here: https://gitlab.inria.fr/Damaris/damaris. You can then follow the instructions for the Damaris Compilation and once compiled and installed, try running one of the many example codes.

If writing your own plugin for use with Damaris then a deep dive into the C++ API available can be accessed through the dOxygen reference pages. Be sure to look at the already available plugins for examples of how to access data (e.g. HDF5) on the Damaris server side processes. Typically, you need to loop over Variables, and then from the Variables you need to access their Block data structures. Simple really!

Short History

Damaris was at the core of the PhD thesis of Matthieu Dorier, who received an Accessit to the Gilles Kahn Ph.D. Thesis Award of the SIF and the Academy of Science in 2015. Developed in the framework of our collaboration with the JLESC – Joint Laboratory for Extreme-Scale Computing, Damaris was the first software resulted from this joint lab validated in 2011 for integration to the Blue Waters supercomputer project. It scaled up to 16,000 cores on Oak Ridge’s leadership supercomputer Titan (first in the Top500 supercomputer list in 2013) before being validated on other top supercomputers. Active development is currently continuing within the KerData team at Inria, where it is at the center of several collaborations with industry as well as with national and international academic partners.

Why Damaris?

Most HPC simulations work through a series of iterations, generating a large dataset on each iteration, as a result:

• They trigger a heavy I/O burst at each iteration, that leads to inefficient I/O management and unpredictable variability in performance and execution time, also known as jitter.
• In the usual approach, the datasets are shipped to some auxiliary post-processing platforms for analysis and visualization.
• The mentioned data transfer is very costly, and no output is available until the end of the post-processing analysis and visualization phase.

Solution

As a solution to the mentioned problem, Damaris, that is a middleware for data management targeting large-scale, HPC simulations is designed. HPC simulations can benefit from Damaris by:

• “In situ” data analysis and visualization by some dedicated cores/nodes of the simulation platform, in parallel with the computation
• Asynchronous and fast data transfer from HPC simulation applications to Damaris using Damaris APIs
• Semantic-aware simulation dataset processing by extending Damaris through plug-ins

Benefits

Use Cases

Those simulation applications that model complex structures, dynamics, phenomena or behaviors, in order to predict their specific concerns to the highest possible degree of precision, can be considered as a beneficiary of Damaris.

• Computer Aided Engineering
• Geophysics and Oil Applications
• Weather Prediction and Tornado Simulation
• Numerical Analysis
• Aerospace Studies,
• Chemical and Pharmaceutical Studies,
• Energy Research,
• Computational Fluid Dynamics

Technologies