https://github.com/tpapp/objectpools.jl

An implementation of user-managed object pools in Julia.
https://github.com/tpapp/objectpools.jl

Last synced: over 1 year ago
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An implementation of user-managed object pools in Julia.

• Host: GitHub
• URL: https://github.com/tpapp/objectpools.jl
• Owner: tpapp
• License: other
• Created: 2019-11-04T13:50:17.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-12-20T09:17:26.000Z (over 5 years ago)
• Last Synced: 2025-02-28T16:20:12.234Z (over 1 year ago)
• Language: Julia
• Size: 4.88 KB
• Stars: 6
• Watchers: 3
• Forks: 2
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# ObjectPools.jl

![Lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)

[![Build Status](https://travis-ci.com/tpapp/ObjectPools.jl.svg?branch=master)](https://travis-ci.com/tpapp/ObjectPools.jl)

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An implementation of user-managed object pools in Julia.

# Overview

This package is designed for use cases where some *inner* functions would need to allocate a large number of arrays which would not escape an outer function `f`. An object pool allows the user to obtain new objects with the `new!`, then allow them to be recycled with `recycle!`.

Consider this (contrived) example:

```julia

function f(pool, x::AbstractVector{T}) where T

    recycle!(pool)                   # reuse all arrays

    S = float(T)

    l = length(x)

    y = new!(pool, Vector{S}, l)     # taken from pool

    z = new!(pool, Matrix{S}, l, l)  # taken from pool

    @. y = abs2(x)

    z .= x .+ permutedims(x)

    z * y                            # the only allocated array

end

```

`pool = ArrayPool()` will save the relevant interim arrays and avoid allocation when necessary. If the function is called with various types, these will eventually accumulate too in `pool`.