heyoka 0.17.0

[bluescarni]

This new version of heyoka comes with a big new feature, several quality-of-life improvements and a few fixes.

Ensemble propagations 🚀

The big new feature is support for ensemble propagations. In ensemble mode, multiple distinct instances of the same ODE system are integrated in parallel, typically using different sets of initial conditions and/or runtime parameters. Monte Carlo simulations and parameter searches are two typical examples of tasks in which ensemble mode is particularly useful.

The combination of ensemble mode with batch integrators can lead to substantial speedups (e.g., a floating-point throughput increase of 23x was observed on a modern desktop computer using 8 threads of execution).

Note that, at this time, ensemble mode is limited to using multithreading for parallelisation.

Quality of life improvements

• Several functions in the batch integration API now also accept scalar time values in input, instead of just vectors. This change improves the usability of batch mode by reducing the amount of typing necessary to interact with batch integrators;
• a function to compute the suggested SIMD size for the CPU in use was added;
• it is now possible to access the internal representation of the integrator's time variable as a double-length float;
• the LLVM version number against which heyoka was built is now exported in the CMake config-file package. This information is intended to be used by packages depending on heyoka to avoid inadvertently linking together different versions of LLVM.

Fixes 🐞

• A couple of build failures were fixed;
• a potential issue arising when certain data structures related to event detection are destroyed in the wrong order has been corrected.

The full changelog, as usual, is available here:

https://bluescarni.github.io/heyoka/changelog.html

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This discussion was created from the release heyoka 0.17.0.