# Importing Plots increasing garbage collection

**URL:** <https://discourse.julialang.org/t/importing-plots-increasing-garbage-collection/89878>\
**Category:** General Usage\
**Tags:** plots\
**Created:** [November 7, 2022, 1:33pm UTC](https://discourse.julialang.org/t/importing-plots-increasing-garbage-collection/89878 "2022-11-07T13:33:11Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![jewh](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jewh/32/28586_2.png) [@jewh](https://discourse.julialang.org/u/jewh)\
**Post date:** [November 7, 2022, 1:33pm UTC](https://discourse.julialang.org/t/importing-plots-increasing-garbage-collection/89878/1 "2022-11-07T13:33:11Z")

</div>

It seems that importing Plots is significantly increasing the mean % garbage collection time when executing this function `motif2`. Does anyone know why, and how to prevent it?

```julia
julia> using BenchmarkTools

julia> function motif2(v::Vector{Vector{Float64}})     
           out = Vector{Float64}(undef, sum(length, v))
           offset = 0
           for vect in v
               for i ∈ eachindex(vect)
                   @inbounds out[offset + i] = vect[i] 
               end
               offset += lastindex(vect)
           end
           out
       end
motif2 (generic function with 1 method)

julia> vects = [rand(10) for i = 1:10];

julia> @benchmark motif2($vects)
BenchmarkTools.Trial: 10000 samples with 984 evaluations.
 Range (min … max): 54.675 ns … 1.503 μs ┊ GC (min … max): 0.00% … 63.57%
 Time (median): 76.321 ns ┊ GC (median): 0.00%
 Time (mean ± σ): 97.977 ns ± 78.032 ns ┊ GC (mean ± σ): 6.96% ± 9.13%

   ▆█▆▄▄▃▃▃▂▂▁▁ ▂
  ██████████████▇█▇██▇██▆█▇▇▆▆▆▆▅▅▄▅▃▄▁▄▅▅▆▆▅▅▆▆▄▅▄▄▃▅▄▄▄▅▆▅▅ █
  54.7 ns Histogram: log(frequency) by time 539 ns <

 Memory estimate: 896 bytes, allocs estimate: 1.

julia> using Plots

julia> @benchmark motif2($vects)
BenchmarkTools.Trial: 7273 samples with 978 evaluations.
 Range (min … max): 69.734 ns … 44.415 μs ┊ GC (min … max): 0.00% … 99.23%
 Time (median): 87.628 ns ┊ GC (median): 0.00%
 Time (mean ± σ): 704.629 ns ± 4.747 μs ┊ GC (mean ± σ): 77.36% ± 11.30%

  █ ▁
  █▆▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▇ █
  69.7 ns Histogram: log(frequency) by time 41.4 μs <

 Memory estimate: 896 bytes, allocs estimate: 1.

julia> versioninfo()
Julia Version 1.8.2
Commit 36034abf26 (2022-09-29 15:21 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 16 × 11th Gen Intel(R) Core(TM) i7-11800H @ 2.30GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, tigerlake)
  Threads: 16 on 16 virtual cores
Environment:
  JULIA_EDITOR = code
  JULIA_NUM_THREADS = 16

```

This is partially replicable, e.g. on a remote (linux) machine I see an increase in % GC time, though not quite to the extent I’m seeing on my local machine (the example above):

```julia
julia> using BenchmarkTools

julia> function motif2(v::Vector{Vector{Float64}})
           out = Vector{Float64}(undef, sum(length, v))
           offset = 0
           for vect in v
               for i ∈ eachindex(vect)
                   @inbounds out[offset + i] = vect[i]
               end
               offset += lastindex(vect)
           end
           out
       end
motif2 (generic function with 1 method)

julia> vects = [rand(10) for i = 1:10];

julia> @benchmark motif2($vects)
BenchmarkTools.Trial: 10000 samples with 719 evaluations.
 Range (min … max): 150.026 ns … 15.705 μs ┊ GC (min … max): 0.00% … 0.00%
 Time (median): 198.854 ns ┊ GC (median): 0.00%
 Time (mean ± σ): 242.629 ns ± 289.033 ns ┊ GC (mean ± σ): 4.84% ± 7.61%

  ▄█▇▆▅▃▁ ▂
  ███████▇▇▇▇▇▆▅▅▆▅▅▅▅▅▆▆▆▄▅▃▄▁▃▄▃▁▃▁▄▄▃▄▅▄▅▅▅▆▆▅▄▆▅▅▆▅▄▅▆▆▄▄▄▅ █
  150 ns Histogram: log(frequency) by time 1.52 μs <

 Memory estimate: 896 bytes, allocs estimate: 1.

julia> using Plots

julia> @benchmark motif2($vects)
BenchmarkTools.Trial: 10000 samples with 695 evaluations.
 Range (min … max): 156.403 ns … 11.613 μs ┊ GC (min … max): 0.00% … 0.00%
 Time (median): 202.976 ns ┊ GC (median): 0.00%
 Time (mean ± σ): 293.527 ns ± 390.842 ns ┊ GC (mean ± σ): 11.85% ± 9.58%

  █▇▅▅▃▁ ▁▂▂▂ ▂
  ██████▆▇▆▆██████▇▇▇▇▆▅▁▁▁▃▃▁▁▁▁▁▁▁▁▃▁▁▁▁▁▁▁▁▁▁▁▃▁▁▁▁▁▁▄▄▅▅▅▅▅ █
  156 ns Histogram: log(frequency) by time 2.81 μs <

 Memory estimate: 896 bytes, allocs estimate: 1.

julia> @benchmark motif2($vects)
BenchmarkTools.Trial: 10000 samples with 888 evaluations.
 Range (min … max): 167.446 ns … 12.581 μs ┊ GC (min … max): 0.00% … 0.00%
 Time (median): 196.846 ns ┊ GC (median): 0.00%
 Time (mean ± σ): 272.220 ns ± 340.188 ns ┊ GC (mean ± σ): 12.18% ± 10.38%

  █▇ ▁▃▂▂ ▁
  ███▇▇▇▆▆▆▆▆▇█████▄▄▁▁▁▁▁▁▁▁▁▁▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▄▄▄▅▅▅▆▅▆▆▆ █
  167 ns Histogram: log(frequency) by time 2.43 μs <

 Memory estimate: 896 bytes, allocs estimate: 1.

julia> versioninfo()
Julia Version 1.8.2
Commit 36034abf260 (2022-09-29 15:21 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × Intel(R) Xeon(R) CPU E5-2640 v4 @ 2.40GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, broadwell)
  Threads: 1 on 4 virtual cores
Environment:
  LD_LIBRARY_PATH = /apps/system/easybuild/software/Julia/1.8.2-linux-x86_64/lib

```

Although % GC is quantitatively quite different on the two machines, it seems that there’s a consistent increase after importing Plots. Any ideas as to why?

---

<div class="post-metadata">

**Author:** ![jewh](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jewh/32/28586_2.png) [@jewh](https://discourse.julialang.org/u/jewh)\
**Post date:** [November 7, 2022, 1:34pm UTC](https://discourse.julialang.org/t/importing-plots-increasing-garbage-collection/89878/2 "2022-11-07T13:34:09Z")

</div>

Worth noting that removing and re-adding Plots has no effect, on either machine

---

<div class="post-metadata">

**Author:** ![baggepinnen](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/baggepinnen/32/693_2.png) [@baggepinnen](https://discourse.julialang.org/u/baggepinnen)\
**Post date:** [November 7, 2022, 1:44pm UTC](https://discourse.julialang.org/t/importing-plots-increasing-garbage-collection/89878/3 "2022-11-07T13:44:56Z")

</div>

It looks like this _could_ be due to a single slow run where the GC was triggered and might have done a full sweep. If you look at the second benchmark, the maximum time is about 10x larger than the median time, this will have a large effect on the mean. The median is probably a more robust estimator here.

There still appears to be somewhat of a difference though, since all times have increased slightly.

---

<div class="post-metadata">

**Author:** ![jewh](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jewh/32/28586_2.png) [@jewh](https://discourse.julialang.org/u/jewh)\
**Post date:** [November 7, 2022, 1:57pm UTC](https://discourse.julialang.org/t/importing-plots-increasing-garbage-collection/89878/4 "2022-11-07T13:57:01Z")

</div>

Yeah I think the fact there’s an increase across the board is perplexing