Optimizing Serial Code In Julia 1 Memory Models Mutation And Vectorization

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Deep Overview

In this video we make small changes to our N body simulation example to show various easy Lessons learned while achieving a 100x speedup of TrajectoryOptimization.jl by eliminating allocations.

Overview Next Steps

In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course. This talk was presented as part of JuliaCon2021 Abstract: Modern databases can choose between two approaches to evaluating ... You might not know all of the latest methods in differential equations, all of the best knobs to tweak, how to properly handle ...

Resource Related Context

You might not know all of the latest methods in differential equations, all of the best knobs to tweak, how to properly handle ... SIMD (Single Instruction, Multiple Data) is a term for when the processor executes the same operation (like addition) on multiple ...

Relevant Notes

Important details can vary by source, so this page groups the most readable points into a scannable format.

Key points worth scanning

• In this video we make small changes to our N body simulation example to show various easy
• You might not know all of the latest methods in differential equations, all of the best knobs to tweak, how to properly handle ...
• SIMD (Single Instruction, Multiple Data) is a term for when the processor executes the same operation (like addition) on multiple ...
• This talk was presented as part of JuliaCon2021 Abstract: Modern databases can choose between two approaches to evaluating ...
• In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course.

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