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Benchmark Report

Job Properties

Commit: JuliaLang/julia@323e725c1e4848414b5642b8f54c24916b9ddd9e

Comparison Range: link

Triggered By: link

Tag Predicate: ALL

Daily Job: 2024-07-05 vs 2024-06-14

Results

Note: If Chrome is your browser, I strongly recommend installing the Wide GitHub extension, which makes the result table easier to read.

Below is a table of this job's results, obtained by running the benchmarks found in JuliaCI/BaseBenchmarks.jl. The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.

The percentages accompanying time and memory values in the below table are noise tolerances. The "true" time/memory value for a given benchmark is expected to fall within this percentage of the reported value.

A ratio greater than 1.0 denotes a possible regression (marked with ❌), while a ratio less than 1.0 denotes a possible improvement (marked with ✅). Only significant results - results that indicate possible regressions or improvements - are shown below (thus, an empty table means that all benchmark results remained invariant between builds).

ID time ratio memory ratio
["alloc", "strings"] 1.05 (5%) ❌ 1.16 (1%) ❌
["array", "accumulate", ("accumulate!", "Int")] 1.08 (5%) ❌ 1.00 (1%)
["array", "accumulate", ("cumsum!", "Int")] 1.08 (5%) ❌ 1.00 (1%)
["array", "cat", ("catnd", 5)] 0.94 (5%) ✅ 1.00 (1%)
["array", "cat", ("vcat", 5)] 1.10 (5%) ❌ 1.00 (1%)
["array", "cat", ("vcat_setind", 5)] 1.10 (5%) ❌ 1.00 (1%)
["array", "equality", ("==", "BitArray")] 1.37 (5%) ❌ 1.00 (1%)
["array", "equality", ("==", "UnitRange{Int64}")] 1.20 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "UnitRange{Int64}")] 1.10 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Float32}")] 0.93 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Float64}")] 0.91 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Int64}")] 0.92 (5%) ✅ 1.00 (1%)
["array", "index", "2d"] 0.88 (5%) ✅ 1.00 (1%)
["array", "index", ("sumcartesian_view", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.23 (50%) ❌ 1.00 (1%)
["array", "index", ("sumcartesian_view", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 2.24 (50%) ❌ 1.00 (1%)
["array", "index", ("sumcolon_view", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.23 (50%) ❌ 1.00 (1%)
["array", "index", ("sumcolon_view", "SubArray{Int32, 2, Base.ReshapedArray{Int32, 2, SubArray{Int32, 3, Array{Int32, 3}, Tuple{Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}, Tuple{}}, Tuple{Base.Slice{Base.OneTo{Int64}}, UnitRange{Int64}}, true}")] 3.06 (50%) ❌ 1.00 (1%)
["array", "index", ("sumcolon_view", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 2.27 (50%) ❌ 1.00 (1%)
["array", "index", ("sumcolon_view", "SubArray{Int32, 2, Matrix{Int32}, Tuple{UnitRange{Int64}, UnitRange{Int64}}, false}")] 2.25 (50%) ❌ 1.00 (1%)
["array", "index", ("sumeach", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.58 (50%) ❌ 1.00 (1%)
["array", "index", ("sumeach", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 2.26 (50%) ❌ 1.00 (1%)
["array", "index", ("sumeach_view", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.59 (50%) ❌ 1.00 (1%)
["array", "index", ("sumeach_view", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 2.22 (50%) ❌ 1.00 (1%)
["array", "index", ("sumelt", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 1.97 (50%) ❌ 1.00 (1%)
["array", "index", ("sumlinear", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.58 (50%) ❌ 1.00 (1%)
["array", "index", ("sumlinear_view", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.59 (50%) ❌ 1.00 (1%)
["array", "index", ("sumrange_view", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 2.27 (50%) ❌ 1.00 (1%)
["array", "index", ("sumrange_view", "SubArray{Int32, 2, Base.ReshapedArray{Int32, 2, SubArray{Int32, 3, Array{Int32, 3}, Tuple{Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}, Tuple{}}, Tuple{Base.Slice{Base.OneTo{Int64}}, UnitRange{Int64}}, true}")] 3.07 (50%) ❌ 1.00 (1%)
["array", "index", ("sumrange_view", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 2.23 (50%) ❌ 1.00 (1%)
["array", "index", ("sumrange_view", "SubArray{Int32, 2, Matrix{Int32}, Tuple{UnitRange{Int64}, UnitRange{Int64}}, false}")] 2.27 (50%) ❌ 1.00 (1%)
["array", "reductions", ("sumabs2", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["array", "reverse", "rev_load_fast!"] 0.95 (5%) ✅ 1.00 (1%)
["array", "setindex!", ("setindex!", 1)] 1.07 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 3)] 1.07 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 5)] 0.93 (5%) ✅ 1.00 (1%)
["array", "subarray", ("lucompletepivCopy!", 100)] 1.05 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivCopy!", 1000)] 1.05 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivCopy!", 250)] 1.05 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivCopy!", 500)] 1.05 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivSub!", 100)] 1.06 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivSub!", 1000)] 1.10 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivSub!", 250)] 1.09 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivSub!", 500)] 1.10 (5%) ❌ 1.00 (1%)
["broadcast", "dotop", ("Float64", "(1000, 1000)", 2)] 1.28 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup")] 1.09 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup_x3")] 1.06 (5%) ❌ 1.00 (1%)
["broadcast", "sparse", ("(1000, 1000)", 2)] 0.93 (5%) ✅ 1.00 (1%)
["dates", "accessor", "millisecond"] 0.85 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("Date", "Day")] 0.91 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Day")] 0.91 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Hour")] 1.10 (5%) ❌ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Millisecond")] 0.91 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Second")] 1.10 (5%) ❌ 1.00 (1%)
["dates", "conversion", "Date -> DateTime"] 1.22 (5%) ❌ 1.00 (1%)
["dates", "parse", ("Date", "DateFormat")] 1.11 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Bool}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Int8}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Float32}")] 1.05 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{Float32}")] 1.09 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.99", "Vector{Float32}")] 1.09 (5%) ❌ 1.00 (1%)
["find", "findall", ("BitVector", "50-50")] 0.91 (5%) ✅ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "10-90")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "50-50")] 0.89 (5%) ✅ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "90-10")] 1.05 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Float32}")] 1.12 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Int8}")] 1.11 (5%) ❌ 1.00 (1%)
["inference", "abstract interpretation", "many_opaque_closures"] 1.00 (5%) 0.99 (1%) ✅
["inference", "allinference", "Base.init_stdio(::Ptr{Cvoid})"] 1.04 (5%) 1.01 (1%) ❌
["inference", "optimization", "many_local_vars"] 1.09 (5%) ❌ 1.00 (1%)
["inference", "optimization", "println(::QuoteNode)"] 1.07 (5%) ❌ 1.00 (1%)
["io", "array_limit", ("display", "Matrix{Float64}(10000, 10000)")] 0.98 (5%) 0.99 (1%) ✅
["io", "array_limit", ("display", "Matrix{Float64}(100000000, 1)")] 0.94 (5%) ✅ 0.93 (1%) ✅
["io", "array_limit", ("display", "Vector{Float64}(100000000,)")] 0.94 (5%) ✅ 0.93 (1%) ✅
["io", "serialization", ("deserialize", "Matrix{Float64}")] 1.09 (5%) ❌ 1.00 (1%)
["io", "skipchars"] 1.00 (5%) 1.02 (1%) ❌
["misc", "23042", "Float64"] 1.05 (5%) ❌ 1.00 (1%)
["misc", "bitshift", ("Int", "Int")] 0.92 (5%) ✅ 1.00 (1%)
["misc", "bitshift", ("Int", "UInt")] 0.93 (5%) ✅ 1.00 (1%)
["misc", "bitshift", ("UInt", "UInt")] 0.92 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1, 1:1)"] 1.09 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000)"] 1.06 (5%) ❌ 1.00 (1%)
["problem", "imdb", "centrality"] 1.01 (5%) 0.99 (1%) ✅
["problem", "laplacian", "laplace_iter_sub"] 1.09 (5%) ❌ 1.00 (1%)
["problem", "laplacian", "laplace_iter_vec"] 1.12 (5%) ❌ 1.00 (1%)
["random", "ranges", ("rand", "MersenneTwister", "UInt32", "RangeGenerator(1:1)")] 1.76 (25%) ❌ 1.00 (1%)
["scalar", "acos", ("0.5 <= abs(x) < 1", "negative argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "atan", ("0 <= abs(x) < 7/16", "negative argument", "Float64")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("very large", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "atan", ("very large", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "atan", ("very small", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "atan", ("very small", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "atan", ("zero", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "atan2", ("x one", "Float32")] 1.46 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("x one", "Float64")] 0.60 (5%) ✅ 1.00 (1%)
["scalar", "atanh", ("2^-28 <= abs(x) < 0.5", "negative argument", "Float64")] 1.86 (5%) ❌ 1.00 (1%)
["scalar", "cbrt", ("large", "negative argument", "Float32")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "cbrt", ("zero", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "cosh", ("0 <= abs(x) < 0.00024414062f0", "negative argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "exp2", ("2pow1023", "positive argument", "Float64")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("arg reduction I", "negative argument", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("arg reduction I", "positive argument", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("arg reduction II", "negative argument", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("arg reduction II", "positive argument", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("large", "positive argument", "Float64")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("one", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("small", "positive argument", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 2.0^20π/4", "negative argument", "Float64")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 2.0^20π/4", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 3π/4", "negative argument", "Float64")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "sin", ("argument reduction (easy) abs(x) < 2.0^20π/4", "negative argument", "Float64", "sin_kernel")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (easy) abs(x) < 2.0^20π/4", "positive argument", "Float64", "sin_kernel")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("large", "positive argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["simd", ("Cartesian", "conditional_loop!", "Int32", 2, 32)] 1.24 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "inner", "Float64", 3, 64)] 0.71 (20%) ✅ 1.00 (1%)
["simd", ("Cartesian", "inner", "Int32", 2, 31)] 1.29 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "inner", "Int32", 2, 63)] 1.34 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "inner", "Int32", 3, 31)] 1.29 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "two_reductions", "Float64", 3, 64)] 0.70 (20%) ✅ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 2, 63)] 0.60 (20%) ✅ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 3, 31)] 1.35 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 4, 31)] 1.20 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 4, 32)] 0.71 (20%) ✅ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 4, 64)] 0.71 (20%) ✅ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int64", 2, 31)] 1.25 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int64", 4, 32)] 0.70 (20%) ✅ 1.00 (1%)
["simd", ("Linear", "auto_conditional_loop!", "Int32", 4096)] 1.20 (20%) ❌ 1.00 (1%)
["sort", "insertionsort", "sort! reverse"] 1.35 (20%) ❌ 1.00 (1%)
["sort", "issues", "inplace sorting of a view"] 1.20 (20%) ❌ 1.00 (1%)
["sort", "issues", "partialsort!(rand(10_000), 1:3, rev=true)"] 0.99 (20%) 1.03 (1%) ❌
["sort", "length = 1000", "sort!(rand(Int, length))"] 1.22 (20%) ❌ 1.00 (1%)
["sparse", "constructors", ("IJV", 10)] 0.92 (5%) ✅ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt!", "sparse 400x400, dense 400x400 -> dense 400x400")] 1.31 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt!", "sparse 40x40, dense 4000x40 -> dense 40x4000")] 1.33 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt", "sparse 500x500, dense 5x500 -> dense 500x5")] 1.53 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt", "sparse 50x50, dense 50x50 -> dense 50x50")] 1.42 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt", "sparse 50x500, dense 5x500 -> dense 50x5")] 1.63 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt", "sparse 5x50, dense 50x50 -> dense 5x50")] 1.47 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_Bt!", "dense 400x40, sparse 4000x400 -> dense 40x4000")] 0.70 (30%) ✅ 1.00 (1%)
["sparse", "matmul", ("At_mul_Bt", "dense 50x5, sparse 500x50 -> dense 5x500")] 1.33 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_Bt", "dense 5x5, sparse 500x5 -> dense 5x500")] 1.51 (30%) ❌ 1.00 (1%)
["string", "==(::AbstractString, ::AbstractString)", "identical"] 0.73 (5%) ✅ 1.00 (1%)
["string", "==(::SubString, ::String)", "different length"] 1.09 (5%) ❌ 1.00 (1%)
["string", "readuntil", "target length 2"] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "index", ("sumelt", "NTuple", 3, "Float64")] 1.50 (40%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(16, 16)", "(16, 16)")] 1.16 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(4, 4)", "(4, 4)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(2, 2)", "(2,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "misc", "11899"] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(2, 2)")] 1.06 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(4,)")] 0.81 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(8, 8)")] 1.14 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(4,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(8,)")] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "ComplexF64", "(false, true)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Float32", 1)] 1.28 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Int8", 1)] 1.17 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "BigInt", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float32", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float32", 1)] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Int8", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "BigInt", 0)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "Bool", 1)] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Float64", 1)] 1.14 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "ComplexF64", "(false, true)")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float32", "(false, true)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float64", "(false, true)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "abs", "Float32", 1)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "abs", "Float64", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "BigInt", 0)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Bool", 1)] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Float64", 1)] 1.15 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float32", "(true, true)")] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int8", "(false, true)")] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int8", "(true, true)")] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigInt", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Bool", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Int8", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum", "BigFloat", 0)] 1.36 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "BigFloat", 1)] 1.35 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "Int64", 0)] 0.72 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum", "Int64", 1)] 0.72 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum2", "Int64", 0)] 0.72 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum2", "Int64", 1)] 0.72 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "BigFloat", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "BigFloat", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Float32", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float64", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Int64", 0)] 0.72 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum4", "Int64", 1)] 0.72 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum4", "Int8", 0)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Bool", 0)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Int8}", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "BigFloat", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Int64", 0)] 0.48 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Missing, BigFloat}", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Missing, Bool}", 1)] 1.18 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Missing, ComplexF64}", 1)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Missing, Float64}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Missing, Int8}", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "BigFloat", 0)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Int64", 0)] 0.66 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Union{Missing, BigFloat}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Union{Missing, Int64}", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("sort", "Float32", 0)] 1.08 (5%) ❌ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["alloc"]
  • ["array", "accumulate"]
  • ["array", "any/all"]
  • ["array", "bool"]
  • ["array", "cat"]
  • ["array", "comprehension"]
  • ["array", "convert"]
  • ["array", "equality"]
  • ["array", "growth"]
  • ["array", "index"]
  • ["array", "reductions"]
  • ["array", "reverse"]
  • ["array", "setindex!"]
  • ["array", "subarray"]
  • ["broadcast"]
  • ["broadcast", "dotop"]
  • ["broadcast", "fusion"]
  • ["broadcast", "mix_scalar_tuple"]
  • ["broadcast", "sparse"]
  • ["broadcast", "typeargs"]
  • ["collection", "deletion"]
  • ["collection", "initialization"]
  • ["collection", "iteration"]
  • ["collection", "optimizations"]
  • ["collection", "queries & updates"]
  • ["collection", "set operations"]
  • ["dates", "accessor"]
  • ["dates", "arithmetic"]
  • ["dates", "construction"]
  • ["dates", "conversion"]
  • ["dates", "parse"]
  • ["dates", "query"]
  • ["dates", "string"]
  • ["find", "findall"]
  • ["find", "findnext"]
  • ["find", "findprev"]
  • ["frontend"]
  • ["inference", "abstract interpretation"]
  • ["inference", "allinference"]
  • ["inference", "optimization"]
  • ["io", "array_limit"]
  • ["io", "read"]
  • ["io", "serialization"]
  • ["io"]
  • ["linalg", "arithmetic"]
  • ["linalg", "blas"]
  • ["linalg", "factorization"]
  • ["linalg"]
  • ["micro"]
  • ["misc"]
  • ["misc", "23042"]
  • ["misc", "afoldl"]
  • ["misc", "allocation elision view"]
  • ["misc", "bitshift"]
  • ["misc", "foldl"]
  • ["misc", "issue 12165"]
  • ["misc", "iterators"]
  • ["misc", "julia"]
  • ["misc", "parse"]
  • ["misc", "repeat"]
  • ["misc", "splatting"]
  • ["problem", "chaosgame"]
  • ["problem", "fem"]
  • ["problem", "go"]
  • ["problem", "grigoriadis khachiyan"]
  • ["problem", "imdb"]
  • ["problem", "json"]
  • ["problem", "laplacian"]
  • ["problem", "monte carlo"]
  • ["problem", "raytrace"]
  • ["problem", "seismic"]
  • ["problem", "simplex"]
  • ["problem", "spellcheck"]
  • ["problem", "stockcorr"]
  • ["problem", "ziggurat"]
  • ["random", "collections"]
  • ["random", "randstring"]
  • ["random", "ranges"]
  • ["random", "sequences"]
  • ["random", "types"]
  • ["scalar", "acos"]
  • ["scalar", "acosh"]
  • ["scalar", "arithmetic"]
  • ["scalar", "asin"]
  • ["scalar", "asinh"]
  • ["scalar", "atan"]
  • ["scalar", "atan2"]
  • ["scalar", "atanh"]
  • ["scalar", "cbrt"]
  • ["scalar", "cos"]
  • ["scalar", "cosh"]
  • ["scalar", "exp2"]
  • ["scalar", "expm1"]
  • ["scalar", "fastmath"]
  • ["scalar", "floatexp"]
  • ["scalar", "intfuncs"]
  • ["scalar", "iteration"]
  • ["scalar", "mod2pi"]
  • ["scalar", "predicate"]
  • ["scalar", "rem_pio2"]
  • ["scalar", "sin"]
  • ["scalar", "sincos"]
  • ["scalar", "sinh"]
  • ["scalar", "tan"]
  • ["scalar", "tanh"]
  • ["shootout"]
  • ["simd"]
  • ["sort", "insertionsort"]
  • ["sort", "issorted"]
  • ["sort", "issues"]
  • ["sort", "length = 10"]
  • ["sort", "length = 100"]
  • ["sort", "length = 1000"]
  • ["sort", "length = 10000"]
  • ["sort", "length = 3"]
  • ["sort", "length = 30"]
  • ["sort", "mergesort"]
  • ["sort", "quicksort"]
  • ["sparse", "arithmetic"]
  • ["sparse", "constructors"]
  • ["sparse", "index"]
  • ["sparse", "matmul"]
  • ["sparse", "sparse matvec"]
  • ["sparse", "sparse solves"]
  • ["sparse", "transpose"]
  • ["string", "==(::AbstractString, ::AbstractString)"]
  • ["string", "==(::SubString, ::String)"]
  • ["string", "findfirst"]
  • ["string"]
  • ["string", "readuntil"]
  • ["string", "repeat"]
  • ["tuple", "index"]
  • ["tuple", "linear algebra"]
  • ["tuple", "misc"]
  • ["tuple", "reduction"]
  • ["union", "array"]

Version Info

Primary Build

Julia Version 1.12.0-DEV.768
Commit 323e725c1e (2024-06-22 18:05 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.4 LTS
  uname: Linux 5.15.0-112-generic #122-Ubuntu SMP Thu May 23 07:48:21 UTC 2024 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1  3501 MHz      55042 s         21 s      20733 s   22410586 s          0 s
       #2  3500 MHz     589694 s         30 s      22681 s   21879226 s          0 s
       #3  3501 MHz      29600 s         48 s      11947 s   22448571 s          0 s
       #4  3500 MHz      30522 s         32 s      14846 s   22435033 s          0 s
       #5  3503 MHz      21511 s         18 s      10012 s   22439788 s          0 s
       #6  3829 MHz      27600 s          8 s      14074 s   22330611 s          0 s
       #7  3744 MHz      29176 s         28 s      11696 s   22427213 s          0 s
       #8  3764 MHz      23168 s         20 s       9644 s   22447949 s          0 s
  Memory: 31.30148696899414 GB (25294.9921875 MB free)
  Uptime: 2.25019678e6 sec
  Load Avg:  1.0  1.02  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-17.0.6 (ORCJIT, haswell)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)