# Help me on strange performance slow down using SMatrix

**URL:** <https://discourse.julialang.org/t/help-me-on-strange-performance-slow-down-using-smatrix/23027>\
**Category:** Performance\
**Created:** [April 11, 2019, 10:37am UTC](https://discourse.julialang.org/t/help-me-on-strange-performance-slow-down-using-smatrix/23027 "2019-04-11T10:37:11Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![Roger-luo](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/roger-luo/32/3399_2.png) [@Roger-luo](https://discourse.julialang.org/u/Roger-luo)\
**Post date:** [April 11, 2019, 10:37am UTC](https://discourse.julialang.org/t/help-me-on-strange-performance-slow-down-using-smatrix/23027/1 "2019-04-11T10:37:11Z")

</div>

```julia
function instruct2!(state, U, loc)
    a, c, b, d = U
    step = 1 << (loc - 1)
    step_2 = 1 << loc
    for j in 0:step_2:size(state, 1)-step
       for i in j+1:j+step
            u1rows!(state, i, i+step, a, b, c, d)
       end
    end
    return state
end

@inline @inbounds function u1rows!(state::AbstractVector, i::Int, j::Int, a, b, c, d)
    w = state[i]
    v = state[j]
    state[i] = a*w+b*v
    state[j] = c*w+d*v
    state
end

```

I’m using `SMatrix` instead of `Matrix` for a small matrix (2x2), the only related operations are `iterate_index`, which looks like `a, b, c, d = U` (U is the matrix), the rest of the code is only related to `a, b, c, d`, but the performance seems not to, the difference between `SMatrix` and `Matrix` increases along with the size of state

I tested this on Julia

```julia
Julia Version 1.1.0
Commit 80516ca202 (2019-01-21 21:24 UTC)
Platform Info:
  OS: macOS (x86_64-apple-darwin18.2.0)
  CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
  WORD_SIZE: 64
  LIBM: libimf
  LLVM: libLLVM-6.0.1 (ORCJIT, skylake)
Environment:
  JULIA_EDITOR = code

```

```julia
julia> @benchmark foreach(k->instruct2!($st, $U, 1), 1:100)
BenchmarkTools.Trial:
  memory estimate: 0 bytes
  allocs estimate: 0
  --------------
  minimum time: 183.067 ms (0.00% GC)
  median time: 191.323 ms (0.00% GC)
  mean time: 192.796 ms (0.00% GC)
  maximum time: 209.240 ms (0.00% GC)
  --------------
  samples: 26
  evals/sample: 1

julia> @benchmark foreach(k->instruct2!($st, $(Matrix(U)), 1), 1:100)
BenchmarkTools.Trial:
  memory estimate: 0 bytes
  allocs estimate: 0
  --------------
  minimum time: 178.031 ms (0.00% GC)
  median time: 181.558 ms (0.00% GC)
  mean time: 184.131 ms (0.00% GC)
  maximum time: 219.924 ms (0.00% GC)
  --------------
  samples: 28
  evals/sample: 1

```

But this looks unexpected since the main cost has nothing to do with which kind of matrix type to use…

---

<div class="post-metadata">

**Author:** ![kristoffer.carlsson](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/kristoffer.carlsson/32/22_2.png) [@kristoffer.carlsson](https://discourse.julialang.org/u/kristoffer.carlsson)\
**Post date:** [April 11, 2019, 10:45am UTC](https://discourse.julialang.org/t/help-me-on-strange-performance-slow-down-using-smatrix/23027/2 "2019-04-11T10:45:39Z")

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Please provide enough code so that the benchmarks can be run, preferably with just copy and paste.

Also, there is no need to do a `foreach` loop for benchmarking, BenchmarkTools does that for your. The time difference seems very small as well.

---

<div class="post-metadata">

**Author:** ![Roger-luo](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/roger-luo/32/3399_2.png) [@Roger-luo](https://discourse.julialang.org/u/Roger-luo)\
**Post date:** [April 11, 2019, 7:00pm UTC](https://discourse.julialang.org/t/help-me-on-strange-performance-slow-down-using-smatrix/23027/3 "2019-04-11T19:00:29Z")

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sorry, I missed first two lines:

```julia
using StaticArrays, BenchmarkTools

U = @SMatrix rand(ComplexF64, 2, 2)
st = rand(ComplexF64, 1<<20)

```

The overhead is small indeed, but it is somehow seems not to be constant on my laptop, it scales with the total time cost (when increase the size of `state`), and `instruct!` function is actually inside another for loop, so it’s pretty obvious when there’s a loop, like a few ms.

In fact, if I just measure the time cost of `a, b, c, d = U`, `SMatrix` is much faster, which make this look strange to me.