performancepaper VS icfpc2019

There is a review of the study at https://github.com/joinr/performancepaper. Basically by using optimization tricks (recur for recursive function call, unchecked math, using Java types, etc.) Tom meets/beats the performance of Java.

I did a contrast with someone's graduate thesis that aimed to analyze clojure vs. java performance and made some weak claims. The rep is here, and it's really the org file. Sort of a worked example of optimizing code.

I often see people knocking on Clojure saying its performance is bad when they are still not familiar with all the core library has to offer and what idiomatic performant Clojure can look like. Take a look here for some examples by joinr

Regarding hashing, custom hash functions even for records (if all fields are longs for example) can help substantially if you are hashing points some notes here. Even then, depending on what you are doing, you may be better off using a primitive numeric representation and a dense collection (e.g. a primitive array) since the mechanical sympathy may be substantial. It is also possible to do well using nested maps (particularly for memoization) when the pieces of a compound key are already trivially hashed. E.g. clojure.core/memoize just defines a varargs wrapper around a function and caches the sequence of args in a map. For earlier reasons, this is a poor strategy for many functions and performance can be substantially improved (e.g. for a 1 or 2 arg function of numbers or keys or strings even) if we defined fixed arity paths that store keys in nested maps instead of hashing complex collections.

There's a worked example of optimizing an ICFPC2019 entry here where the readme goes through a bevy of techniques and observations.