Video How To Reduce Julia S Latency Community Julia Programming Minimise julia's latency: revise, precompiletools, and packagecompiler jmms 84 subscribers subscribed. Again, i feel like that’s asking more of my prospective users than they would likely stomach. for end user applications, i usually provide a script that performs the package compiler step as part of “installation”. i did some analysis of the loading time for these two packages for you.
Are Revise Packagecompiler And Pkg Part Of Julia And How Do We Precompiletools allows you to reduce the latency of the first execution of julia code. it is applicable for package developers and for "ordinary users" in their personal workflows. If the latency of spinning up new threads becomes a bottleneck, check out polyester.jl for very lightweight threads that are quicker to start. if you're on linux, you should consider using threadpinning.jl to pin your julia threads to cpu cores to obtain stable and optimal performance. You can use precompiletools as a package developer, to reduce the latency experienced by users of your package for "typical" workloads; you can also use precompiletools as a user, creating custom "startup" package (s) that precompile workloads important for your work. Precompiletools allows you to reduce the latency of the first execution of julia code. it is applicable for package developers and for "ordinary users" in their personal workflows. to learn how to use precompiletools, see the documentation.
Are Revise Packagecompiler And Pkg Part Of Julia And How Do We You can use precompiletools as a package developer, to reduce the latency experienced by users of your package for "typical" workloads; you can also use precompiletools as a user, creating custom "startup" package (s) that precompile workloads important for your work. Precompiletools allows you to reduce the latency of the first execution of julia code. it is applicable for package developers and for "ordinary users" in their personal workflows. to learn how to use precompiletools, see the documentation. You can do two things to reduce the latency: use julia 1.5.0 (beta as of today) it dynamically allows to use different optimization levels for packages and plots.jl is making use of that reducing the time to first plot by more than half. As of 2023, to reduce latency, i recommend the following steps: make sure your package don’t commit type piracy. you can use aqua.jl to detect some (most?) cases of type piracy automatically. make sure your code is inferrible (i.e. all variables are type stable in your functions). Packagecompiler allows you to do this work upfront — further ahead of time — and store the results for a lower latency startup. there are three main workflows: you can save loaded packages and compiled functions into a file (called a sysimage) that you pass to julia upon startup. How can i reduce julia's startup latency? precompile functions into custom packages, minimize dependencies, and use packagecompiler.jl to build a system image if needed.
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