# Marching cubes without extra allocations

**URL:** https://discourse.julialang.org/t/marching-cubes-without-extra-allocations/6222
**Category:** General Usage
**Created:** [October 3, 2017, 4:03pm UTC](https://discourse.julialang.org/t/marching-cubes-without-extra-allocations/6222 "2017-10-03T16:03:02Z")
**Posts on this page:** 1
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### Author: ![rdeits](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/rdeits/32/286_2.png) [@rdeits](https://discourse.julialang.org/u/rdeits)
#### Post date: [October 3, 2017, 6:45pm UTC](https://discourse.julialang.org/t/marching-cubes-without-extra-allocations/6222/2 "2017-10-03T18:45:56Z")

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I would suggest first trying to rewrite the code to operate on views rather than slices, which might help you modularize the algorithm. Constructing a `view()` will allocate less memory than copying out a slice of an array, although it still allocates some. Fortunately, I think there’s some cool work underway to make non-allocating views possible in Julia v0.7.

Until then, if you find that your algorithm is cleaner with `view`s, and if you want to remove the small memory allocation that each `view` creates, it’s possible to make an unsafe view-like object that allocates no memory at all. One example is here: [https://github.com/rdeits/NNLS.jl/blob/b7314fb9691a9d4ec9897316c8732f9aba94ed47/src/NNLS.jl#L200](https://github.com/rdeits/NNLS.jl/blob/b7314fb9691a9d4ec9897316c8732f9aba94ed47/src/NNLS.jl#L200) (based on earlier work by `@tkoolen` and `@jrevels`). This object is “unsafe” because if you keep the `UnsafeVectorView` around after its parent goes out of scope, then you may end up with a view of junk data. But it’s otherwise ideal for constructing lots of extremely cheap views within the inner loop of an algorithm. For example, I use these unsafe views in NNLS.jl here: [https://github.com/rdeits/NNLS.jl/blob/b7314fb9691a9d4ec9897316c8732f9aba94ed47/src/NNLS.jl#L342](https://github.com/rdeits/NNLS.jl/blob/b7314fb9691a9d4ec9897316c8732f9aba94ed47/src/NNLS.jl#L342) to efficiently grab views of my `A` matrix to pass to the `construct_householder!` function which expects an `AbstractVector`. This means that `construct_householder!` doesn’t need to know anything about the indices of `A`, but I also have no memory allocation penalty at all.

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