heyoka 0.16.0 #219
bluescarni
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This is another big release for heyoka, featuring 2 major new features and substantial performance improvements.
Event detection support in batch mode ⏩
Event detection is now available in the batch mode Taylor integrator. As a result, the batch mode integrator has now feature parity with the scalar mode integrator.
The batch mode event detection API is very similar to scalar mode. A tutorial describing the new feature is available here:
https://bluescarni.github.io/heyoka/tut_batch_mode.html#event-detection
Continuous output 📈
Debuting in this release is support for continuous output for the
propagate_for/until()
functions of the scalar and batch integrators.Continuous output allows to compute the value of the solution of the ODE system at any time within the integration time interval covered by
propagate_for/until()
. Tutorials are available here:https://bluescarni.github.io/heyoka/tut_d_output.html#continuous-output
https://bluescarni.github.io/heyoka/tut_batch_mode.html#dense-continuous-output
This feature has been inspired by a similar feature available in the DifferentialEquations.jl package.
Performance improvements 🚀
As a result of various micro-optimisations, performance for large ODE systems in compact mode has improved by up to 15%.
Additionally, fast event exclusion checking is now implemented as a JIT-compiled function, which leads to a ~30% reduction in the event detection overhead.
Miscellanea ☑️
The full changelog, as usual, is available here:
https://bluescarni.github.io/heyoka/changelog.html
This discussion was created from the release heyoka 0.16.0.
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