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mbauman/Manifest.toml

Created October 11, 2019 18:54
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Fast partitions
Raw
bench.jl
import Random
using BenchmarkTools
Random.seed!(0)
println("branch, type, len, dims, desc, time")
for n in round.(Int, 10.0.^(0.5:0.5:5))
for T in (Int8, Int32, Int64)
for (desc, dims) in (("1d", (100n,)),
("2d (wide)", (10, 10n)),
("2d (tall)", (10n, 10)),
(n > 10 ? (("3d (wide)", (10, 10, n)),
("3d (tall)", (n, 10, 10)),) : ())...)
a = rand(T(0):T(4), dims)
b = @benchmark $a .== $(T(0))
println("$(Base.GIT_VERSION_INFO.branch)-$(Base.GIT_VERSION_INFO.commit_short), $T, $(100n), $(Base.dims2string(dims)), $desc, $(minimum(b).time)")
end
end
end
Raw
change.csv
branch type len dims desc time
mb/fast-partitions-9fe93b6b52 Int8 300 300-element 1d 505.7368421052632
mb/fast-partitions-9fe93b6b52 Int8 300 10×30 2d (wide) 817.4074074074074
mb/fast-partitions-9fe93b6b52 Int8 300 30×10 2d (tall) 728.8076923076923
mb/fast-partitions-9fe93b6b52 Int32 300 300-element 1d 511.4842105263158
mb/fast-partitions-9fe93b6b52 Int32 300 10×30 2d (wide) 794.7820512820513
mb/fast-partitions-9fe93b6b52 Int32 300 30×10 2d (tall) 687.1044776119403
mb/fast-partitions-9fe93b6b52 Int64 300 300-element 1d 541.2967032967033
mb/fast-partitions-9fe93b6b52 Int64 300 10×30 2d (wide) 807.9180327868852
mb/fast-partitions-9fe93b6b52 Int64 300 30×10 2d (tall) 685.0142857142857
mb/fast-partitions-9fe93b6b52 Int8 1000 1000-element 1d 570.8474576271186
mb/fast-partitions-9fe93b6b52 Int8 1000 10×100 2d (wide) 1367.4
mb/fast-partitions-9fe93b6b52 Int8 1000 100×10 2d (tall) 1097.1
mb/fast-partitions-9fe93b6b52 Int32 1000 1000-element 1d 589.393063583815
mb/fast-partitions-9fe93b6b52 Int32 1000 10×100 2d (wide) 1368.2
mb/fast-partitions-9fe93b6b52 Int32 1000 100×10 2d (tall) 567.0
mb/fast-partitions-9fe93b6b52 Int64 1000 1000-element 1d 598.0057142857142
mb/fast-partitions-9fe93b6b52 Int64 1000 10×100 2d (wide) 1162.6
mb/fast-partitions-9fe93b6b52 Int64 1000 100×10 2d (tall) 699.6382978723404
mb/fast-partitions-9fe93b6b52 Int8 3200 3200-element 1d 732.9469026548672
mb/fast-partitions-9fe93b6b52 Int8 3200 10×320 2d (wide) 3015.3333333333335
mb/fast-partitions-9fe93b6b52 Int8 3200 320×10 2d (tall) 919.2941176470588
mb/fast-partitions-9fe93b6b52 Int8 3200 10×10×32 3d (wide) 3341.0
mb/fast-partitions-9fe93b6b52 Int8 3200 32×10×10 3d (tall) 2311.222222222222
mb/fast-partitions-9fe93b6b52 Int32 3200 3200-element 1d 797.6627906976744
mb/fast-partitions-9fe93b6b52 Int32 3200 10×320 2d (wide) 2836.0
mb/fast-partitions-9fe93b6b52 Int32 3200 320×10 2d (tall) 1042.7878787878788
mb/fast-partitions-9fe93b6b52 Int32 3200 10×10×32 3d (wide) 3287.75
mb/fast-partitions-9fe93b6b52 Int32 3200 32×10×10 3d (tall) 1304.3
mb/fast-partitions-9fe93b6b52 Int64 3200 3200-element 1d 1144.3
mb/fast-partitions-9fe93b6b52 Int64 3200 10×320 2d (wide) 2948.3333333333335
mb/fast-partitions-9fe93b6b52 Int64 3200 320×10 2d (tall) 1195.0
mb/fast-partitions-9fe93b6b52 Int64 3200 10×10×32 3d (wide) 3503.375
mb/fast-partitions-9fe93b6b52 Int64 3200 32×10×10 3d (tall) 1696.9
mb/fast-partitions-9fe93b6b52 Int8 10000 10000-element 1d 1448.7
mb/fast-partitions-9fe93b6b52 Int8 10000 10×1000 2d (wide) 8172.0
mb/fast-partitions-9fe93b6b52 Int8 10000 1000×10 2d (tall) 1950.0
mb/fast-partitions-9fe93b6b52 Int8 10000 10×10×100 3d (wide) 9924.0
mb/fast-partitions-9fe93b6b52 Int8 10000 100×10×10 3d (tall) 6222.4
mb/fast-partitions-9fe93b6b52 Int32 10000 10000-element 1d 2058.777777777778
mb/fast-partitions-9fe93b6b52 Int32 10000 10×1000 2d (wide) 8312.333333333334
mb/fast-partitions-9fe93b6b52 Int32 10000 1000×10 2d (tall) 2245.5555555555557
mb/fast-partitions-9fe93b6b52 Int32 10000 10×10×100 3d (wide) 10463.0
mb/fast-partitions-9fe93b6b52 Int32 10000 100×10×10 3d (tall) 2946.875
mb/fast-partitions-9fe93b6b52 Int64 10000 10000-element 1d 3069.25
mb/fast-partitions-9fe93b6b52 Int64 10000 10×1000 2d (wide) 8689.333333333334
mb/fast-partitions-9fe93b6b52 Int64 10000 1000×10 2d (tall) 3344.375
mb/fast-partitions-9fe93b6b52 Int64 10000 10×10×100 3d (wide) 9928.0
mb/fast-partitions-9fe93b6b52 Int64 10000 100×10×10 3d (tall) 3944.375
mb/fast-partitions-9fe93b6b52 Int8 31600 31600-element 1d 4024.25
mb/fast-partitions-9fe93b6b52 Int8 31600 10×3160 2d (wide) 27009.0
mb/fast-partitions-9fe93b6b52 Int8 31600 3160×10 2d (tall) 4726.714285714285
mb/fast-partitions-9fe93b6b52 Int8 31600 10×10×316 3d (wide) 31532.0
mb/fast-partitions-9fe93b6b52 Int8 31600 316×10×10 3d (tall) 7566.0
mb/fast-partitions-9fe93b6b52 Int32 31600 31600-element 1d 5743.833333333333
mb/fast-partitions-9fe93b6b52 Int32 31600 10×3160 2d (wide) 24818.0
mb/fast-partitions-9fe93b6b52 Int32 31600 3160×10 2d (tall) 6143.6
mb/fast-partitions-9fe93b6b52 Int32 31600 10×10×316 3d (wide) 30454.0
mb/fast-partitions-9fe93b6b52 Int32 31600 316×10×10 3d (tall) 7244.5
mb/fast-partitions-9fe93b6b52 Int64 31600 31600-element 1d 9746.0
mb/fast-partitions-9fe93b6b52 Int64 31600 10×3160 2d (wide) 26910.0
mb/fast-partitions-9fe93b6b52 Int64 31600 3160×10 2d (tall) 10097.0
mb/fast-partitions-9fe93b6b52 Int64 31600 10×10×316 3d (wide) 31193.0
mb/fast-partitions-9fe93b6b52 Int64 31600 316×10×10 3d (tall) 10835.0
mb/fast-partitions-9fe93b6b52 Int8 100000 100000-element 1d 10950.0
mb/fast-partitions-9fe93b6b52 Int8 100000 10×10000 2d (wide) 85029.0
mb/fast-partitions-9fe93b6b52 Int8 100000 10000×10 2d (tall) 12819.0
mb/fast-partitions-9fe93b6b52 Int8 100000 10×10×1000 3d (wide) 94409.0
mb/fast-partitions-9fe93b6b52 Int8 100000 1000×10×10 3d (tall) 18345.0
mb/fast-partitions-9fe93b6b52 Int32 100000 100000-element 1d 19346.0
mb/fast-partitions-9fe93b6b52 Int32 100000 10×10000 2d (wide) 80820.0
mb/fast-partitions-9fe93b6b52 Int32 100000 10000×10 2d (tall) 19480.0
mb/fast-partitions-9fe93b6b52 Int32 100000 10×10×1000 3d (wide) 119935.0
mb/fast-partitions-9fe93b6b52 Int32 100000 1000×10×10 3d (tall) 20791.0
mb/fast-partitions-9fe93b6b52 Int64 100000 100000-element 1d 30852.0
mb/fast-partitions-9fe93b6b52 Int64 100000 10×10000 2d (wide) 86473.0
mb/fast-partitions-9fe93b6b52 Int64 100000 10000×10 2d (tall) 31410.0
mb/fast-partitions-9fe93b6b52 Int64 100000 10×10×1000 3d (wide) 101355.0
mb/fast-partitions-9fe93b6b52 Int64 100000 1000×10×10 3d (tall) 32690.0
mb/fast-partitions-9fe93b6b52 Int8 316200 316200-element 1d 37736.0
mb/fast-partitions-9fe93b6b52 Int8 316200 10×31620 2d (wide) 275615.0
mb/fast-partitions-9fe93b6b52 Int8 316200 31620×10 2d (tall) 40986.0
mb/fast-partitions-9fe93b6b52 Int8 316200 10×10×3162 3d (wide) 292809.0
mb/fast-partitions-9fe93b6b52 Int8 316200 3162×10×10 3d (tall) 45495.0
mb/fast-partitions-9fe93b6b52 Int32 316200 316200-element 1d 61359.0
mb/fast-partitions-9fe93b6b52 Int32 316200 10×31620 2d (wide) 249321.0
mb/fast-partitions-9fe93b6b52 Int32 316200 31620×10 2d (tall) 65554.0
mb/fast-partitions-9fe93b6b52 Int32 316200 10×10×3162 3d (wide) 305377.0
mb/fast-partitions-9fe93b6b52 Int32 316200 3162×10×10 3d (tall) 67147.0
mb/fast-partitions-9fe93b6b52 Int64 316200 316200-element 1d 99976.0
mb/fast-partitions-9fe93b6b52 Int64 316200 10×31620 2d (wide) 272499.0
mb/fast-partitions-9fe93b6b52 Int64 316200 31620×10 2d (tall) 101770.0
mb/fast-partitions-9fe93b6b52 Int64 316200 10×10×3162 3d (wide) 321255.0
mb/fast-partitions-9fe93b6b52 Int64 316200 3162×10×10 3d (tall) 106196.0
mb/fast-partitions-9fe93b6b52 Int8 1000000 1000000-element 1d 116514.0
mb/fast-partitions-9fe93b6b52 Int8 1000000 10×100000 2d (wide) 848126.0
mb/fast-partitions-9fe93b6b52 Int8 1000000 100000×10 2d (tall) 122757.0
mb/fast-partitions-9fe93b6b52 Int8 1000000 10×10×10000 3d (wide) 944257.0
mb/fast-partitions-9fe93b6b52 Int8 1000000 10000×10×10 3d (tall) 129902.0
mb/fast-partitions-9fe93b6b52 Int32 1000000 1000000-element 1d 185631.0
mb/fast-partitions-9fe93b6b52 Int32 1000000 10×100000 2d (wide) 816185.0
mb/fast-partitions-9fe93b6b52 Int32 1000000 100000×10 2d (tall) 195551.0
mb/fast-partitions-9fe93b6b52 Int32 1000000 10×10×10000 3d (wide) 987265.0
mb/fast-partitions-9fe93b6b52 Int32 1000000 10000×10×10 3d (tall) 196799.0
mb/fast-partitions-9fe93b6b52 Int64 1000000 1000000-element 1d 349197.0
mb/fast-partitions-9fe93b6b52 Int64 1000000 10×100000 2d (wide) 886240.0
mb/fast-partitions-9fe93b6b52 Int64 1000000 100000×10 2d (tall) 366252.0
mb/fast-partitions-9fe93b6b52 Int64 1000000 10×10×10000 3d (wide) 1.067073e6
mb/fast-partitions-9fe93b6b52 Int64 1000000 10000×10×10 3d (tall) 371938.0
mb/fast-partitions-9fe93b6b52 Int8 3162300 3162300-element 1d 363686.0
mb/fast-partitions-9fe93b6b52 Int8 3162300 10×316230 2d (wide) 2.576279e6
mb/fast-partitions-9fe93b6b52 Int8 3162300 316230×10 2d (tall) 399517.0
mb/fast-partitions-9fe93b6b52 Int8 3162300 10×10×31623 3d (wide) 2.920456e6
mb/fast-partitions-9fe93b6b52 Int8 3162300 31623×10×10 3d (tall) 429756.0
mb/fast-partitions-9fe93b6b52 Int32 3162300 3162300-element 1d 1.01465e6
mb/fast-partitions-9fe93b6b52 Int32 3162300 10×316230 2d (wide) 2.596813e6
mb/fast-partitions-9fe93b6b52 Int32 3162300 316230×10 2d (tall) 922455.0
mb/fast-partitions-9fe93b6b52 Int32 3162300 10×10×31623 3d (wide) 3.154745e6
mb/fast-partitions-9fe93b6b52 Int32 3162300 31623×10×10 3d (tall) 945142.0
mb/fast-partitions-9fe93b6b52 Int64 3162300 3162300-element 1d 1.670366e6
mb/fast-partitions-9fe93b6b52 Int64 3162300 10×316230 2d (wide) 2.832679e6
mb/fast-partitions-9fe93b6b52 Int64 3162300 316230×10 2d (tall) 1.675325e6
mb/fast-partitions-9fe93b6b52 Int64 3162300 10×10×31623 3d (wide) 3.388998e6
mb/fast-partitions-9fe93b6b52 Int64 3162300 31623×10×10 3d (tall) 1.730335e6
mb/fast-partitions-9fe93b6b52 Int8 10000000 10000000-element 1d 1.618404e6
mb/fast-partitions-9fe93b6b52 Int8 10000000 10×1000000 2d (wide) 8.404793e6
mb/fast-partitions-9fe93b6b52 Int8 10000000 1000000×10 2d (tall) 1.812859e6
mb/fast-partitions-9fe93b6b52 Int8 10000000 10×10×100000 3d (wide) 9.09645e6
mb/fast-partitions-9fe93b6b52 Int8 10000000 100000×10×10 3d (tall) 1.850639e6
mb/fast-partitions-9fe93b6b52 Int32 10000000 10000000-element 1d 3.475826e6
mb/fast-partitions-9fe93b6b52 Int32 10000000 10×1000000 2d (wide) 8.233927e6
mb/fast-partitions-9fe93b6b52 Int32 10000000 1000000×10 2d (tall) 3.456597e6
mb/fast-partitions-9fe93b6b52 Int32 10000000 10×10×100000 3d (wide) 9.786834e6
mb/fast-partitions-9fe93b6b52 Int32 10000000 100000×10×10 3d (tall) 3.835078e6
mb/fast-partitions-9fe93b6b52 Int64 10000000 10000000-element 1d 5.674091e6
mb/fast-partitions-9fe93b6b52 Int64 10000000 10×1000000 2d (wide) 9.538401e6
mb/fast-partitions-9fe93b6b52 Int64 10000000 1000000×10 2d (tall) 5.703097e6
mb/fast-partitions-9fe93b6b52 Int64 10000000 10×10×100000 3d (wide) 1.0244907e7
mb/fast-partitions-9fe93b6b52 Int64 10000000 100000×10×10 3d (tall) 5.731882e6
Display the source blob
Display the rendered blob
Raw
diff.svg
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Raw
Manifest.toml
# This file is machine-generated - editing it directly is not advised
[[AbstractFFTs]]
deps = ["LinearAlgebra"]
git-tree-sha1 = "380e36c66edfa099cd90116b24c1ce8cafccac40"
uuid = "621f4979-c628-5d54-868e-fcf4e3e8185c"
version = "0.4.1"
[[Arpack]]
deps = ["BinaryProvider", "Libdl", "LinearAlgebra"]
git-tree-sha1 = "07a2c077bdd4b6d23a40342a8a108e2ee5e58ab6"
uuid = "7d9fca2a-8960-54d3-9f78-7d1dccf2cb97"
version = "0.3.1"
[[ArrayInterface]]
deps = ["LinearAlgebra", "Requires", "SparseArrays"]
git-tree-sha1 = "981354dab938901c2b607a213e62d9defa50b698"
uuid = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
version = "1.2.1"
[[AxisAlgorithms]]
deps = ["LinearAlgebra", "Random", "SparseArrays", "WoodburyMatrices"]
git-tree-sha1 = "a4d07a1c313392a77042855df46c5f534076fab9"
uuid = "13072b0f-2c55-5437-9ae7-d433b7a33950"
version = "1.0.0"
[[Base64]]
uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
[[BinDeps]]
deps = ["Compat", "Libdl", "SHA", "URIParser"]
git-tree-sha1 = "12093ca6cdd0ee547c39b1870e0c9c3f154d9ca9"
uuid = "9e28174c-4ba2-5203-b857-d8d62c4213ee"
version = "0.8.10"
[[BinaryProvider]]
deps = ["Libdl", "Logging", "SHA"]
git-tree-sha1 = "c7361ce8a2129f20b0e05a89f7070820cfed6648"
uuid = "b99e7846-7c00-51b0-8f62-c81ae34c0232"
version = "0.5.6"
[[CSV]]
deps = ["CategoricalArrays", "DataFrames", "Dates", "Mmap", "Parsers", "PooledArrays", "Profile", "Tables", "Unicode", "WeakRefStrings"]
git-tree-sha1 = "5e7c67bc2873b347cd20ee742c93d243f3df9e93"
uuid = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
version = "0.5.13"
[[Calculus]]
deps = ["Compat"]
git-tree-sha1 = "bd8bbd105ba583a42385bd6dc4a20dad8ab3dc11"
uuid = "49dc2e85-a5d0-5ad3-a950-438e2897f1b9"
version = "0.5.0"
[[CategoricalArrays]]
deps = ["Compat", "DataAPI", "Future", "JSON", "Missings", "Printf", "Reexport", "Unicode"]
git-tree-sha1 = "45101c4d0df3946acb6e9bfcfd3a8c32abbd421b"
uuid = "324d7699-5711-5eae-9e2f-1d82baa6b597"
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version = "0.6.1"
[[Widgets]]
deps = ["Colors", "Dates", "Observables", "OrderedCollections"]
git-tree-sha1 = "fc0feda91b3fef7fe6948ee09bb628f882b49ca4"
uuid = "cc8bc4a8-27d6-5769-a93b-9d913e69aa62"
version = "0.6.2"
[[WoodburyMatrices]]
deps = ["LinearAlgebra", "Random", "SparseArrays", "Test"]
git-tree-sha1 = "21772c33b447757ec7d3e61fcdfb9ea5c47eedcf"
uuid = "efce3f68-66dc-5838-9240-27a6d6f5f9b6"
version = "0.4.1"
Raw
master.csv
branch type len dims desc time
master-b30047137e Int8 300 300-element 1d 601.3157894736842
master-b30047137e Int8 300 10×30 2d (wide) 738.9
master-b30047137e Int8 300 30×10 2d (tall) 719.1702127659574
master-b30047137e Int32 300 300-element 1d 842.5230769230769
master-b30047137e Int32 300 10×30 2d (wide) 798.448275862069
master-b30047137e Int32 300 30×10 2d (tall) 753.5752212389381
master-b30047137e Int64 300 300-element 1d 755.5272727272727
master-b30047137e Int64 300 10×30 2d (wide) 780.1111111111111
master-b30047137e Int64 300 30×10 2d (tall) 727.297520661157
master-b30047137e Int8 1000 1000-element 1d 1380.5
master-b30047137e Int8 1000 10×100 2d (wide) 1417.0
master-b30047137e Int8 1000 100×10 2d (tall) 1249.8
master-b30047137e Int32 1000 1000-element 1d 1364.4
master-b30047137e Int32 1000 10×100 2d (wide) 1507.8
master-b30047137e Int32 1000 100×10 2d (tall) 1362.0
master-b30047137e Int64 1000 1000-element 1d 1648.1
master-b30047137e Int64 1000 10×100 2d (wide) 1349.9
master-b30047137e Int64 1000 100×10 2d (tall) 1605.6
master-b30047137e Int8 3200 3200-element 1d 3714.5
master-b30047137e Int8 3200 10×320 2d (wide) 2877.777777777778
master-b30047137e Int8 3200 320×10 2d (tall) 3006.0
master-b30047137e Int8 3200 10×10×32 3d (wide) 3522.0
master-b30047137e Int8 3200 32×10×10 3d (tall) 3046.125
master-b30047137e Int32 3200 3200-element 1d 3802.125
master-b30047137e Int32 3200 10×320 2d (wide) 3091.375
master-b30047137e Int32 3200 320×10 2d (tall) 2568.4444444444443
master-b30047137e Int32 3200 10×10×32 3d (wide) 3632.5
master-b30047137e Int32 3200 32×10×10 3d (tall) 3565.3333333333335
master-b30047137e Int64 3200 3200-element 1d 2844.3333333333335
master-b30047137e Int64 3200 10×320 2d (wide) 2969.1111111111113
master-b30047137e Int64 3200 320×10 2d (tall) 2414.8888888888887
master-b30047137e Int64 3200 10×10×32 3d (wide) 3328.625
master-b30047137e Int64 3200 32×10×10 3d (tall) 2907.625
master-b30047137e Int8 10000 10000-element 1d 8414.333333333334
master-b30047137e Int8 10000 10×1000 2d (wide) 8652.0
master-b30047137e Int8 10000 1000×10 2d (tall) 7574.0
master-b30047137e Int8 10000 10×10×100 3d (wide) 10401.0
master-b30047137e Int8 10000 100×10×10 3d (tall) 9224.0
master-b30047137e Int32 10000 10000-element 1d 8846.0
master-b30047137e Int32 10000 10×1000 2d (wide) 10247.0
master-b30047137e Int32 10000 1000×10 2d (tall) 7246.5
master-b30047137e Int32 10000 10×10×100 3d (wide) 10466.0
master-b30047137e Int32 10000 100×10×10 3d (tall) 9225.0
master-b30047137e Int64 10000 10000-element 1d 10741.0
master-b30047137e Int64 10000 10×1000 2d (wide) 8312.0
master-b30047137e Int64 10000 1000×10 2d (tall) 8467.333333333334
master-b30047137e Int64 10000 10×10×100 3d (wide) 10633.0
master-b30047137e Int64 10000 100×10×10 3d (tall) 8301.75
master-b30047137e Int8 31600 31600-element 1d 27352.0
master-b30047137e Int8 31600 10×3160 2d (wide) 25271.0
master-b30047137e Int8 31600 3160×10 2d (tall) 22279.0
master-b30047137e Int8 31600 10×10×316 3d (wide) 31369.0
master-b30047137e Int8 31600 316×10×10 3d (tall) 23280.0
master-b30047137e Int32 31600 31600-element 1d 26734.0
master-b30047137e Int32 31600 10×3160 2d (wide) 28092.0
master-b30047137e Int32 31600 3160×10 2d (tall) 25979.0
master-b30047137e Int32 31600 10×10×316 3d (wide) 30453.0
master-b30047137e Int32 31600 316×10×10 3d (tall) 26639.0
master-b30047137e Int64 31600 31600-element 1d 26448.0
master-b30047137e Int64 31600 10×3160 2d (wide) 28252.0
master-b30047137e Int64 31600 3160×10 2d (tall) 27292.0
master-b30047137e Int64 31600 10×10×316 3d (wide) 33210.0
master-b30047137e Int64 31600 316×10×10 3d (tall) 27282.0
master-b30047137e Int8 100000 100000-element 1d 83669.0
master-b30047137e Int8 100000 10×10000 2d (wide) 90339.0
master-b30047137e Int8 100000 10000×10 2d (tall) 71348.0
master-b30047137e Int8 100000 10×10×1000 3d (wide) 89239.0
master-b30047137e Int8 100000 1000×10×10 3d (tall) 70110.0
master-b30047137e Int32 100000 100000-element 1d 80147.0
master-b30047137e Int32 100000 10×10000 2d (wide) 77732.0
master-b30047137e Int32 100000 10000×10 2d (tall) 79572.0
master-b30047137e Int32 100000 10×10×1000 3d (wide) 106133.0
master-b30047137e Int32 100000 1000×10×10 3d (tall) 74267.0
master-b30047137e Int64 100000 100000-element 1d 84420.0
master-b30047137e Int64 100000 10×10000 2d (wide) 97551.0
master-b30047137e Int64 100000 10000×10 2d (tall) 70511.0
master-b30047137e Int64 100000 10×10×1000 3d (wide) 95722.0
master-b30047137e Int64 100000 1000×10×10 3d (tall) 82191.0
master-b30047137e Int8 316200 316200-element 1d 330227.0
master-b30047137e Int8 316200 10×31620 2d (wide) 250795.0
master-b30047137e Int8 316200 31620×10 2d (tall) 256433.0
master-b30047137e Int8 316200 10×10×3162 3d (wide) 312928.0
master-b30047137e Int8 316200 3162×10×10 3d (tall) 220501.0
master-b30047137e Int32 316200 316200-element 1d 265071.0
master-b30047137e Int32 316200 10×31620 2d (wide) 256347.0
master-b30047137e Int32 316200 31620×10 2d (tall) 268608.0
master-b30047137e Int32 316200 10×10×3162 3d (wide) 319937.0
master-b30047137e Int32 316200 3162×10×10 3d (tall) 234610.0
master-b30047137e Int64 316200 316200-element 1d 272279.0
master-b30047137e Int64 316200 10×31620 2d (wide) 294010.0
master-b30047137e Int64 316200 31620×10 2d (tall) 232404.0
master-b30047137e Int64 316200 10×10×3162 3d (wide) 311880.0
master-b30047137e Int64 316200 3162×10×10 3d (tall) 258951.0
master-b30047137e Int8 1000000 1000000-element 1d 1.067342e6
master-b30047137e Int8 1000000 10×100000 2d (wide) 797373.0
master-b30047137e Int8 1000000 100000×10 2d (tall) 828621.0
master-b30047137e Int8 1000000 10×10×10000 3d (wide) 1.01037e6
master-b30047137e Int8 1000000 10000×10×10 3d (tall) 832310.0
master-b30047137e Int32 1000000 1000000-element 1d 1.062128e6
master-b30047137e Int32 1000000 10×100000 2d (wide) 918413.0
master-b30047137e Int32 1000000 100000×10 2d (tall) 721506.0
master-b30047137e Int32 1000000 10×10×10000 3d (wide) 952197.0
master-b30047137e Int32 1000000 10000×10×10 3d (tall) 702508.0
master-b30047137e Int64 1000000 1000000-element 1d 863252.0
master-b30047137e Int64 1000000 10×100000 2d (wide) 950737.0
master-b30047137e Int64 1000000 100000×10 2d (tall) 737820.0
master-b30047137e Int64 1000000 10×10×10000 3d (wide) 1.014188e6
master-b30047137e Int64 1000000 10000×10×10 3d (tall) 758512.0
master-b30047137e Int8 3162300 3162300-element 1d 2.638417e6
master-b30047137e Int8 3162300 10×316230 2d (wide) 2.864542e6
master-b30047137e Int8 3162300 316230×10 2d (tall) 2.196922e6
master-b30047137e Int8 3162300 10×10×31623 3d (wide) 3.005184e6
master-b30047137e Int8 3162300 31623×10×10 3d (tall) 2.670198e6
master-b30047137e Int32 3162300 3162300-element 1d 2.61103e6
master-b30047137e Int32 3162300 10×316230 2d (wide) 2.978261e6
master-b30047137e Int32 3162300 316230×10 2d (tall) 2.253069e6
master-b30047137e Int32 3162300 10×10×31623 3d (wide) 3.358372e6
master-b30047137e Int32 3162300 31623×10×10 3d (tall) 2.685472e6
master-b30047137e Int64 3162300 3162300-element 1d 3.516202e6
master-b30047137e Int64 3162300 10×316230 2d (wide) 3.030833e6
master-b30047137e Int64 3162300 316230×10 2d (tall) 2.72978e6
master-b30047137e Int64 3162300 10×10×31623 3d (wide) 3.509884e6
master-b30047137e Int64 3162300 31623×10×10 3d (tall) 2.781459e6
master-b30047137e Int8 10000000 10000000-element 1d 8.388876e6
master-b30047137e Int8 10000000 10×1000000 2d (wide) 1.0278511e7
master-b30047137e Int8 10000000 1000000×10 2d (tall) 7.202555e6
master-b30047137e Int8 10000000 10×10×100000 3d (wide) 1.2874222e7
master-b30047137e Int8 10000000 100000×10×10 3d (tall) 7.639029e6
master-b30047137e Int32 10000000 10000000-element 1d 8.803203e6
master-b30047137e Int32 10000000 10×1000000 2d (wide) 9.421469e6
master-b30047137e Int32 10000000 1000000×10 2d (tall) 8.479347e6
master-b30047137e Int32 10000000 10×10×100000 3d (wide) 1.0661995e7
master-b30047137e Int32 10000000 100000×10×10 3d (tall) 8.021657e6
master-b30047137e Int64 10000000 10000000-element 1d 8.980098e6
master-b30047137e Int64 10000000 10×1000000 2d (wide) 9.557138e6
master-b30047137e Int64 10000000 1000000×10 2d (tall) 9.043238e6
master-b30047137e Int64 10000000 10×10×100000 3d (wide) 1.0352854e7
master-b30047137e Int64 10000000 100000×10×10 3d (tall) 8.995436e6
Raw
plot.jl
using CSV, Plots, StatsPlots
master = CSV.read("master.csv", normalizenames=true)
change = CSV.read("change.csv", normalizenames=true)
df = vcat(master, change)
p = @df df[df.desc .== " 1d",:] scatter(:len, :time./1e3, group=(:branch), xscale=:log10, yscale=:log10, legend=:topleft, ylabel="microseconds", xlabel="array length", title="1-dimensional")
savefig(p, "1d.svg")
p = scatter(parse.(Int, first.(split.(change.dims, (['-','×'],)))), change.time ./ master.time, group = change.type, xscale=:log10, ylabel="speed relative master", xlabel="first dimension length")
savefig(p, "diff.svg")
Raw
Project.toml
[deps]
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
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