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MongoDB Atlas runs apps anywhere
Deploy in 115+ regions with the modern database for every enterprise.
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
A co-simulation master for Functional Mockup Units (FMI 1.0 and 2.0).
A simulation master library, command line utility and user interface for simulating coupled systems of Functional Mock-up Units (FMU) for CoSimulation with FMI version 1 and 2.
The master implements several modern algorithms, including Gauss-Seidel, Newton iteration, variable time stepping and step size control.
X-ray and Neutron powder pattern simulation analysis
Keywords (XNDiff):
-SAXS
-SANS
-absolute units
-core (double)shell crystalline nanoparticles -with a parallelepidal shape
-particle assemblies
-powder and ensemble average
-C/C++
-Unix
-OpenMP
-HPC Cluster
Keywords (BatchMultiFit):
-simultaneous fits for several SAXS and SANS curves with simulation data from XNDiff
-SANS data can be smeared with dq values from experimental data sets or analytical functions
-Mathematica console
-local and global optimizers (simulated annealing, differential evolution, Nelder-Mead, ...) can be used
-range for fit parameters and further constraints between fit parameters
-parallelized (typ. 4-8 threads)
TODO (BatchMultiFit):
-read and use errorbars from experimental data sets
-allow different q-ranges for different data sets in the fits
-rewrite and test in Python using e.g. the lmfit module:
https://pypi.python.org/pypi/lmfit/
to get rid of Mathematica and to run it on HPC clusters
ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid
SPLITNEURON is a completely new approach to large-scale, biologically plausible, neural-network simulation library based on data structures and methods directly coded into database and conceived to explicitly share load on multiple machines.
SpiNet is a neural simulation tool for large spiking networks with highly heterogeneous synapses. Neurons are modelled as I&F units with dual exponential synaptic conductances. Complex network models can be easily built using the included tool NetBuilder