As it turns out, this is a perfect application for my persistent vectors
library. I used the following test harness, matching your examples and using
the more “elegant” style of tackling the problem using for loops. I think the
performance speaks for itself.
#lang racket/base
(require
alexis/collection
alexis/pvector)
(define (map-once f ls)
(extend
(pvector)
(for/sequence ([i (in-naturals)]
[elm (in ls)])
(set-nth ls i (f elm)))))
(define (sqr x) (* x x))
(define num-test-cases 10000)
(define num-runs-per-f 3)
(define v (extend (pvector) (take num-test-cases (randoms))))
(displayln "pvector method:")
(for ([__ (in-range num-runs-per-f)])
(time (void (map-once sqr v))))
; OUTPUT
; ----------------------------------------
; pvector method:
; cpu time: 228 real time: 227 gc time: 64
; cpu time: 163 real time: 163 gc time: 71
; cpu time: 122 real time: 121 gc time: 31
Alexis
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