>I hope those benchmarks are coming in hot M1 is extremely good for PDEs because of its large cache lines. https://github.com/SciML/DiffEqOperators.jl/issues/

>I hope those benchmarks are coming in hot M1 is extremely good for PDEs because of its large cache lines. https://github.com/SciML/DiffEqOperators.jl/issues/407#issuecomment-862807968 https://github.com/SciML/DiffEqOperators.jl/issues/407#issue... The JuliaSIMD tools which are internally used for BLAS instead of OpenBLAS and MKL (because they tend to outperform standard BLAS's for the operations we use https://github.com/YingboMa/RecursiveFactorization.jl/pull/28#issuecomment-890267907 https://github.com/YingboMa/RecursiveFactorization.jl/pull/2...) also generate good code for M1, so that was giving us some powerful use cases right off the bat even before the heroics allowed C/Fortran compilers to fully work on M1.