# On OS X Catalina, running 'solve' in DifferentialEquations causes crash

**URL:** <https://discourse.julialang.org/t/on-os-x-catalina-running-solve-in-differentialequations-causes-crash/42109>\
**Category:** General Usage\
**Created:** [June 26, 2020, 2:45pm UTC](https://discourse.julialang.org/t/on-os-x-catalina-running-solve-in-differentialequations-causes-crash/42109 "2020-06-26T14:45:46Z")\
**Posts on this page:** 1\
**Showing post:** 15

<div class="post-metadata">

**Author:** ![Elrod](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/elrod/32/22461_2.png) [@Elrod](https://discourse.julialang.org/u/Elrod)\
**Post date:** [June 27, 2020, 12:21am UTC](https://discourse.julialang.org/t/on-os-x-catalina-running-solve-in-differentialequations-causes-crash/42109/15 "2020-06-27T00:21:06Z")

</div>

In both Julia 1.4 and 1.6, you could try:

```julia
using Pkg
Pkg.add(["RecursiveFactorization", "VegaLite", "DataFrames", "BenchmarkTools"])
using RecursiveFactorization
include(joinpath(pkgdir(RecursiveFactorization), "perf", "lu.jl"))

```

and share your results [here](https://discourse.julialang.org/t/ann-recursivefactorization-jl/39213).

You could also try benchmarking the particular problem you were solving between versions. Solving that problem uses [RecursiveFactorization.jl](https://github.com/YingboMa/RecursiveFactorization.jl).

Something else simple you can try to compare versions:

```julia
using BenchmarkTools
function mysum(x)
    s = zero(eltype(x))
    @simd for xᵢ ∈ x
        s += xᵢ
    end
    s
end
x = rand(128);
@btime mysum($x)

```

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