Uses of non-constant globals can be optimized by annotating their types at the point of use: global x = rand(1000) We find that global names are frequently constants, and declaring them as such greatly improves performance: const DEFAULT_VAL = 0 Variables should be local, or passed as arguments to functions, whenever possible.
#Wise memory optimizer starts two instances at boot up code#
This makes it difficult for the compiler to optimize code using global variables. Avoid global variablesĪ global variable might have its value, and therefore its type, change at any point. The functions should take arguments, instead of operating directly on global variables, see the next point. The use of functions is not only important for performance: functions are more reusable and testable, and clarify what steps are being done and what their inputs and outputs are, Write functions, not just scripts is also a recommendation of Julia's Styleguide. Code inside functions tends to run much faster than top level code, due to how Julia's compiler works. Performance critical code should be inside a functionĪny code that is performance critical should be inside a function. In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible.
The dangers of abusing multiple dispatch (aka, more on types with values-as-parameters).Separate kernel functions (aka, function barriers).Break functions into multiple definitions.Avoid containers with abstract type parameters.
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