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Benchmark Report

Job Properties

Commits: JuliaLang/julia@83180250fcac22f64d8b9006965bc6e36e08cb74 vs JuliaLang/julia@cbcad6f721e88fff829907b51f809ef963fa0a2a

Comparison Diff: link

Triggered By: link

Tag Predicate: !"scalar"

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
["array", "accumulate", ("accumulate", "Int")] 0.92 (5%) ✅ 1.00 (1%)
["array", "accumulate", ("cumsum", "Int")] 0.91 (5%) ✅ 1.00 (1%)
["array", "cat", ("catnd_setind", 5)] 0.95 (5%) ✅ 1.00 (1%)
["array", "cat", ("hvcat", 5)] 0.94 (5%) ✅ 1.00 (1%)
["array", "cat", ("vcat", 5)] 0.94 (5%) ✅ 1.00 (1%)
["array", "convert", ("Complex{Float64}", "Int")] 1.30 (5%) ❌ 1.00 (1%)
["array", "convert", ("Float64", "Int")] 0.67 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal UnitRange{Int64}")] 0.94 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Float32}")] 1.08 (5%) ❌ 1.00 (1%)
["array", "growth", ("push_multiple!", 8)] 0.88 (5%) ✅ 1.00 (1%)
["array", "index", ("sumcolon", "SubArray{Float32, 2, Array{Float32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 1.00 (50%) 1.02 (1%) ❌
["array", "index", ("sumcolon", "SubArray{Float32, 2, Base.ReshapedArray{Float32, 2, SubArray{Float32, 3, Array{Float32, 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}")] 1.51 (50%) ❌ 1.67 (1%) ❌
["array", "index", ("sumcolon", "SubArray{Float32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Float32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 1.00 (50%) 1.02 (1%) ❌
["array", "index", ("sumcolon", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 1.04 (50%) 1.02 (1%) ❌
["array", "index", ("sumcolon", "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}")] 1.63 (50%) ❌ 1.67 (1%) ❌
["array", "index", ("sumcolon", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 1.04 (50%) 1.02 (1%) ❌
["array", "index", ("sumelt_boundscheck", "Base.ReinterpretArray{BaseBenchmarks.ArrayBenchmarks.PairVals{Int32}, 2, Int64, Matrix{Int64}, false}")] 3.44 (50%) ❌ 1.00 (1%)
["array", "index", ("sumelt_boundscheck", "Matrix{Int32}")] 3.99 (50%) ❌ 1.00 (1%)
["array", "index", ("sumelt_boundscheck", "Matrix{Int64}")] 2.11 (50%) ❌ 1.00 (1%)
["array", "index", ("sumrange", "SubArray{Float32, 2, Array{Float32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 1.07 (50%) 1.02 (1%) ❌
["array", "index", ("sumrange", "SubArray{Float32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Float32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 1.08 (50%) 1.02 (1%) ❌
["array", "index", ("sumrange", "SubArray{Int32, 2, Array{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, true}")] 1.10 (50%) 1.02 (1%) ❌
["array", "index", ("sumrange", "SubArray{Int32, 2, BaseBenchmarks.ArrayBenchmarks.ArrayLS{Int32, 3}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Base.Slice{Base.OneTo{Int64}}}, false}")] 1.11 (50%) 1.02 (1%) ❌
["array", "index", ("sumvector_view", "SubArray{Float32, 2, Base.ReshapedArray{Float32, 2, SubArray{Float32, 3, Array{Float32, 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}")] 0.42 (50%) ✅ 1.00 (1%)
["array", "index", ("sumvector_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}")] 0.40 (50%) ✅ 1.00 (1%)
["array", "reductions", ("sumabs2", "Float64")] 1.07 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 3)] 1.07 (5%) ❌ 1.00 (1%)
["array", "subarray", ("gramschmidt!", 100)] 1.21 (5%) ❌ 1.00 (1%)
["array", "subarray", ("gramschmidt!", 1000)] 1.06 (5%) ❌ 1.00 (1%)
["array", "subarray", ("gramschmidt!", 250)] 1.09 (5%) ❌ 1.00 (1%)
["array", "subarray", ("gramschmidt!", 500)] 1.38 (5%) ❌ 1.00 (1%)
["broadcast", "dotop", ("Float64", "(1000, 1000)", 2)] 0.94 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup")] 1.09 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (3, "scal_tup_x3")] 1.08 (5%) ❌ 1.00 (1%)
["collection", "deletion", ("Vector", "Any", "filter!")] 0.73 (25%) ✅ 1.00 (1%)
["dates", "accessor", "millisecond"] 0.92 (5%) ✅ 1.00 (1%)
["dates", "parse", ("Date", "ISODateFormat")] 1.08 (5%) ❌ 1.00 (1%)
["dates", "string", "Date"] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Bool}")] 0.89 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Float32}")] 0.89 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Int8}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{UInt8}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", ("BitVector", "50-50")] 0.88 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Bool}")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Float64}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Int8}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findnext", ("Vector{Bool}", "50-50")] 1.05 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Bool}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Float64}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Int8}")] 0.91 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{UInt64}")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Float64}")] 0.88 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Int8}")] 0.93 (5%) ✅ 1.00 (1%)
["inference", "optimization", "broadcasting"] 0.97 (5%) 0.92 (1%) ✅
["io", "serialization", ("deserialize", "Matrix{Float64}")] 1.09 (5%) ❌ 1.00 (1%)
["linalg", "small exp #29116"] 1.09 (5%) ❌ 1.00 (1%)
["micro", "mandel"] 0.79 (5%) ✅ 1.00 (1%)
["micro", "parseint"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "23042", "Float64"] 1.13 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1)"] 0.92 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1, 1:1, 1:1)"] 1.06 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000, 1:1000)"] 0.94 (5%) ✅ 1.00 (1%)
["misc", "parse", "Float64"] 1.06 (5%) ❌ 1.00 (1%)
["misc", "perf highdim generator"] 1.34 (5%) ❌ 1.00 (1%)
["misc", "repeat", (200, 1, 24)] 1.21 (5%) ❌ 1.00 (1%)
["misc", "repeat", (200, 24, 1)] 1.15 (5%) ❌ 1.00 (1%)
["problem", "go", "go_game"] 0.93 (5%) ✅ 1.00 (1%)
["problem", "laplacian", "laplace_iter_sub"] 0.93 (5%) ✅ 1.00 (1%)
["shootout", "nbody_vec"] 0.88 (5%) ✅ 1.00 (1%)
["simd", ("Cartesian", "conditional_loop!", "Int32", 3, 31)] 1.32 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "conditional_loop!", "Int32", 3, 63)] 1.45 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "inner", "Int32", 4, 31)] 1.21 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 2, 31)] 1.95 (20%) ❌ 1.00 (1%)
["sort", "issues", "partialsort!(rand(10_000), 1:3, rev=true)"] 0.99 (20%) 1.02 (1%) ❌
["sort", "length = 3", "sort!(rand(2n, 2n, n); dims=1)"] 1.27 (20%) ❌ 1.00 (1%)
["sparse", "constructors", ("Bidiagonal", 10)] 0.89 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Bidiagonal", 100)] 0.90 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Diagonal", 100)] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Diagonal", 1000)] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("SymTridiagonal", 10)] 0.90 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Tridiagonal", 10)] 0.91 (5%) ✅ 1.00 (1%)
["string", "==(::SubString, ::String)", "different length"] 0.93 (5%) ✅ 1.00 (1%)
["string", "==(::SubString, ::String)", "different"] 1.05 (5%) ❌ 1.00 (1%)
["string", "readuntil", "target length 1"] 0.94 (5%) ✅ 1.00 (1%)
["string", "repeat", "repeat str len 16"] 0.92 (5%) ✅ 1.00 (1%)
["tuple", "index", ("sumelt", "NTuple", 3, "Float32")] 0.35 (40%) ✅ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(2, 2)", "(2, 2)")] 1.71 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(4, 4)", "(4,)")] 1.08 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(16,)")] 1.29 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(2, 2)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(4, 4)")] 1.32 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(4,)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(8,)")] 0.91 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(2, 2)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(2,)")] 0.93 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(8,)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Bool", "(false, true)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Bool", "(true, true)")] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float64", "(false, true)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float64", "(true, true)")] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Int64", "(false, false)")] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Int64", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "BigFloat", 0)] 0.80 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "BigFloat", 1)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "BigInt", 0)] 0.85 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "BigInt", 1)] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float32", 0)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "BigFloat", 0)] 0.70 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "BigFloat", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "BigInt", 0)] 0.81 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "BigInt", 1)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "filter", "BigFloat", 0)] 0.87 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "filter", "BigFloat", 1)] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "filter", "BigInt", 0)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "filter", "BigInt", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "Float32", "(false, false)")] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "abs", "Int64", 1)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "BigFloat", 0)] 0.70 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "BigFloat", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "BigInt", 0)] 0.81 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "BigInt", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int64", "(false, true)")] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int64", "(true, true)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int8", "(true, true)")] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigFloat", 0)] 0.81 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigFloat", 1)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigInt", 0)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigInt", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Int64", 1)] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "Int8", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "Int8", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum2", "Int8", 0)] 1.14 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Bool", 1)] 0.81 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum4", "Int8", 1)] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "BigFloat", 0)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "BigInt", 0)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, BigFloat}", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, BigInt}", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Int8}", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, BigFloat}", 0)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, BigInt}", 0)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "filter", "Float64", 0)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "filter", "Union{Nothing, Int64}", 0)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "keys", "Union{Missing, BigInt}", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Nothing, Int64}", 0)] 1.21 (5%) ❌ 1.00 (1%)
["union", "array", ("sort", "BigInt", 0)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("sort", "Union{Missing, BigInt}", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("sort", "Union{Nothing, BigInt}", 0)] 0.94 (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"]
  • ["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.1559
Commit 83180250fc (2024-11-05 23:19 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     635830 s        191 s     165111 s  128113573 s          0 s
       #2  3501 MHz    8811623 s        103 s     202752 s  119965017 s          0 s
       #3  3500 MHz     484480 s        127 s      75991 s  128407153 s          0 s
       #4  3501 MHz     472049 s        107 s      91981 s  128345663 s          0 s
       #5  3503 MHz     403726 s         77 s      67204 s  128387215 s          0 s
       #6  3501 MHz     437007 s         64 s      87984 s  127756052 s          0 s
       #7  3501 MHz     468440 s        116 s      72599 s  128308694 s          0 s
       #8  3503 MHz     410260 s         78 s      60084 s  128450696 s          0 s
  Memory: 31.30148696899414 GB (18665.3984375 MB free)
  Uptime: 1.290324557e7 sec
  Load Avg:  1.0  1.0  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-18.1.7 (ORCJIT, haswell)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)

Comparison Build

Julia Version 1.12.0-DEV.1557
Commit cbcad6f721 (2024-11-05 23:02 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  3500 MHz     637510 s        191 s     166032 s  128303420 s          0 s
       #2  3500 MHz    9001500 s        103 s     204650 s  119966111 s          0 s
       #3  3500 MHz     484868 s        127 s      76014 s  128599589 s          0 s
       #4  3500 MHz     472162 s        107 s      91990 s  128538375 s          0 s
       #5  3503 MHz     403778 s         77 s      67207 s  128579863 s          0 s
       #6  3501 MHz     437052 s         64 s      87989 s  127948528 s          0 s
       #7  3501 MHz     468918 s        116 s      72609 s  128501057 s          0 s
       #8  3502 MHz     410337 s         78 s      60090 s  128643456 s          0 s
  Memory: 31.30148696899414 GB (18914.05859375 MB free)
  Uptime: 1.292253253e7 sec
  Load Avg:  1.0  1.0  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-18.1.7 (ORCJIT, haswell)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)