Reference Brief: Lessons learned while achieving a 100x speedup of TrajectoryOptimization.jl by eliminating allocations. In this video we make small changes to our N body simulation example to show various easy optimisation
Juliacon 2020 Optimization Algorithms In Julia For Gpus Michel Schanen - Resource Main Notes
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This workshop covers trendy areas in modern high-performance computing with examples from geoscientific applications. In this video we make small changes to our N body simulation example to show various easy optimisation
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From logistics to bioinformatics or web analytics, graphs are versatile abstractions for modelling problems and solving them with ... Lessons learned while achieving a 100x speedup of TrajectoryOptimization.jl by eliminating allocations.
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- From logistics to bioinformatics or web analytics, graphs are versatile abstractions for modelling problems and solving them with ...
- This workshop covers trendy areas in modern high-performance computing with examples from geoscientific applications.
- Lessons learned while achieving a 100x speedup of TrajectoryOptimization.jl by eliminating allocations.
- In this video we make small changes to our N body simulation example to show various easy optimisation
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![12. Optimisation Tips & Tricks [HPC in Julia]](https://i.ytimg.com/vi/UZzFabpkH8Y/mqdefault.jpg)
