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Benchmark Report

Job Properties

Commit: JuliaLang/julia@320e00db00bb95ab5e7a32bf7e00a5346fecb911

Comparison Range: link

Triggered By: link

Tag Predicate: ALL

Daily Job: 2023-06-13 vs 2023-06-12

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", ("cumsum!", "Int")] 1.32 (5%) ❌ 1.00 (1%)
["array", "bool", "boolarray_bool_load!"] 0.86 (5%) ✅ 1.00 (1%)
["array", "cat", ("catnd", 5)] 1.06 (5%) ❌ 1.00 (1%)
["array", "reverse", "rev_load_fast!"] 0.78 (5%) ✅ 1.00 (1%)
["array", "reverse", "rev_load_slow!"] 0.90 (5%) ✅ 1.00 (1%)
["array", "reverse", "rev_loadmul_fast!"] 0.95 (5%) ✅ 1.00 (1%)
["array", "reverse", "rev_loadmul_slow!"] 0.95 (5%) ✅ 1.00 (1%)
["broadcast", "dotop", ("Float64", "(1000, 1000)", 2)] 0.89 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Int8}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{UInt8}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Bool}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Float32}")] 1.12 (5%) ❌ 1.00 (1%)
["inference", "abstract interpretation", "Base.init_stdio(::Ptr{Cvoid})"] 0.14 (5%) ✅ 0.18 (1%) ✅
["inference", "allinference", "Base.init_stdio(::Ptr{Cvoid})"] 0.16 (5%) ✅ 0.18 (1%) ✅
["io", "read", "readstring"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "23042", "ComplexF32"] 1.11 (5%) ❌ 1.00 (1%)
["misc", "23042", "Float64"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "afoldl", "Int"] 0.87 (5%) ✅ 1.00 (1%)
["random", "ranges", ("RangeGenerator", "BigInt", "1:4294967295")] 1.26 (25%) ❌ 1.00 (1%)
["scalar", "acos", ("0.5 <= abs(x) < 1", "negative argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "asin", ("0.5 <= abs(x) < 0.975", "negative argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", ("0.5 <= abs(x) < 0.975", "negative argument", "Float64")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "asinh", ("very large", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "asinh", ("very large", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "atan2", ("x one", "Float64")] 1.63 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "negative argument", "Float32", "sin_kernel")] 0.86 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "negative argument", "Float64", "sin_kernel")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "positive argument", "Float32", "sin_kernel")] 0.87 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "positive argument", "Float64", "sin_kernel")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "exp2", ("2pow1023", "negative argument", "Float64")] 1.13 (5%) ❌ 1.00 (1%)
["scalar", "exp2", ("2pow1023", "positive argument", "Float64")] 1.13 (5%) ❌ 1.00 (1%)
["scalar", "sin", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "negative argument", "Float32", "cos_kernel")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "negative argument", "Float64", "cos_kernel")] 0.88 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "positive argument", "Float32", "cos_kernel")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (paynehanek) abs(x) > 2.0^20*π/2", "positive argument", "Float64", "cos_kernel")] 0.88 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("medium", "negative argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("0 <= abs(x) < 2.0^-28", "negative argument", "Float64")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("0 <= abs(x) < 2.0^-28", "positive argument", "Float64")] 1.15 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("2.0^-28 <= abs(x) < 1.0", "negative argument", "Float64")] 1.15 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("2.0^-28 <= abs(x) < 1.0", "positive argument", "Float64")] 1.15 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("very small", "positive argument", "Float64")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("zero", "Float64")] 1.15 (5%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 4, 31)] 0.62 (20%) ✅ 1.00 (1%)
["simd", ("CartesianPartition", "manual_partition!", "Int32", 4, 31)] 0.77 (20%) ✅ 1.00 (1%)
["sparse", "sparse matvec", "adjoint"] 0.85 (5%) ✅ 1.00 (1%)
["string", "==(::AbstractString, ::AbstractString)", "identical"] 0.68 (5%) ✅ 1.00 (1%)
["string", "==(::SubString, ::String)", "different"] 0.70 (5%) ✅ 1.00 (1%)
["string", "findfirst", "Char"] 1.10 (5%) ❌ 1.00 (1%)
["string", "readuntil", "target length 1"] 0.92 (5%) ✅ 1.00 (1%)
["string", "repeat", "repeat str len 16"] 0.95 (5%) ✅ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(4, 4)", "(4,)")] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(8, 8)", "(8,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(2, 2)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(2,)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(4,)")] 1.12 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(16,)")] 1.14 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(4, 4)")] 0.92 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(8,)")] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(2,)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Int64", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Bool", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Float32", 1)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "Int64", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Int8", "(true, true)")] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Bool", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Float32", 1)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Int64", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Float32", 1)] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Int64", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum2", "Int8", 1)] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float32", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Float64", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Int64", 1)] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Float64}", 1)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "filter", "BigFloat", 0)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "filter", "Union{Missing, BigFloat}", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "filter", "Union{Nothing, BigFloat}", 0)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Union{Missing, ComplexF64}", 1)] 0.82 (5%) ✅ 1.00 (1%)
["union", "array", ("sort", "Union{Missing, Bool}", 1)] 0.93 (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", "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 1.10.0-DEV.1479
Commit 320e00db00 (2023-06-13 14:33 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.2 LTS
  uname: Linux 5.15.0-58-generic #64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1  3900 MHz     609956 s      50132 s     529949 s  111532408 s          0 s
       #2  3504 MHz   11141961 s      31134 s     586162 s  101193040 s          0 s
       #3  3900 MHz     600294 s      30754 s     412808 s  111849720 s          0 s
       #4  3900 MHz     426842 s      27681 s     376409 s  111781798 s          0 s
  Memory: 31.313323974609375 GB (12974.921875 MB free)
  Uptime: 1.132399293e7 sec
  Load Avg:  1.09  1.05  1.01
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, haswell)
  Threads: 1 on 4 virtual cores