Skip to content

Latest commit

 

History

History
310 lines (291 loc) · 16.7 KB

report.md

File metadata and controls

310 lines (291 loc) · 16.7 KB

Benchmark Report

Job Properties

Commit: JuliaLang/julia@551f3038d959ce3191dd3b0a7e740df01e49c764

Comparison Range: link

Triggered By: link

Tag Predicate: ALL

Daily Job: 2023-03-16 vs 2023-03-13

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")] 1.22 (5%) ❌ 1.00 (1%)
["array", "cat", "4467"] 1.08 (5%) ❌ 1.00 (1%)
["array", "cat", ("hcat_setind", 500)] 1.08 (5%) ❌ 1.00 (1%)
["array", "cat", ("hvcat", 500)] 1.06 (5%) ❌ 1.00 (1%)
["array", "cat", ("hvcat_setind", 500)] 1.07 (5%) ❌ 1.00 (1%)
["array", "cat", ("vcat", 500)] 1.08 (5%) ❌ 1.00 (1%)
["array", "cat", ("vcat_setind", 500)] 1.07 (5%) ❌ 1.00 (1%)
["array", "index", ("sumrange_view", "1.0:0.00010001000100010001:2.0")] 1.52 (50%) ❌ 1.00 (1%)
["array", "reductions", ("perf_reduce", "Int64")] 0.92 (5%) ✅ 1.00 (1%)
["array", "subarray", ("lucompletepivCopy!", 1000)] 1.07 (5%) ❌ 1.00 (1%)
["array", "subarray", ("lucompletepivSub!", 1000)] 1.07 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup_x3")] 1.08 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", ("tuple", 10)] 0.86 (5%) ✅ 1.00 (1%)
["dates", "accessor", "minute"] 1.05 (5%) ❌ 1.00 (1%)
["dates", "parse", ("Date", "DateFormat")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Float32}")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Float64}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Int8}")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{UInt8}")] 0.91 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{Float32}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{UInt8}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", ("BitVector", "50-50")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "90-10")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Int64}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Int8}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{UInt8}")] 0.92 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Float64}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Int8}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{UInt64}")] 0.92 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Bool}")] 0.86 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Float64}")] 0.89 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Int64}")] 0.88 (5%) ✅ 1.00 (1%)
["inference", "abstract interpretation", "Base.init_stdio(::Ptr{Cvoid})"] 1.03 (5%) 1.02 (1%) ❌
["inference", "allinference", "Base.init_stdio(::Ptr{Cvoid})"] 1.02 (5%) 1.02 (1%) ❌
["inference", "optimization", "rand(Float64)"] 0.87 (5%) ✅ 1.00 (1%)
["io", "serialization", ("deserialize", "Matrix{Float64}")] 1.05 (5%) ❌ 1.00 (1%)
["io", "serialization", ("serialize", "Matrix{Float64}")] 0.89 (5%) ✅ 1.00 (1%)
["linalg", "arithmetic", ("+", "typename(LowerTriangular)", "typename(LowerTriangular)", 1024)] 0.53 (45%) ✅ 1.00 (1%)
["misc", "23042", "ComplexF32"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "23042", "Float64"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "afoldl", "Float64"] 1.08 (5%) ❌ 1.00 (1%)
["misc", "fastmath many args"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "issue 12165", "Float16"] 1.16 (5%) ❌ 1.00 (1%)
["misc", "issue 12165", "Float32"] 1.16 (5%) ❌ 1.00 (1%)
["misc", "issue 12165", "Float64"] 1.20 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1)"] 1.05 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1, 1:1, 1:1)"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "asin", ("0.5 <= abs(x) < 0.975", "negative argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("very large", "positive argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("x one", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atanh", ("very small", "negative argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "exp2", ("2pow127", "negative argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "exp2", ("2pow35", "negative argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "intfuncs", ("#3", "UInt64", "+")] 1.25 (25%) ❌ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 4π/4", "negative argument", "Float64")] 1.45 (5%) ❌ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 5π/4", "negative argument", "Float64")] 1.45 (5%) ❌ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 5π/4", "positive argument", "Float64")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sinh", ("2.0^-28 <= abs(x) < 22.0", "negative argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "sinh", ("2.0^-28 <= abs(x) < 22.0", "positive argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "sinh", ("22.0 <= abs(x) < 709.7822265633563", "negative argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "sinh", ("22.0 <= abs(x) < 709.7822265633563", "positive argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "sinh", ("very large", "negative argument", "Float64")] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "sinh", ("very large", "positive argument", "Float64")] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("large", "positive argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("medium", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "tanh", ("zero", "Float32")] 1.21 (5%) ❌ 1.00 (1%)
["shootout", "binary_trees"] 0.91 (5%) ✅ 1.00 (1%)
["sort", "issorted", ("reverse", "random")] 1.66 (30%) ❌ 1.00 (1%)
["sparse", "constructors", ("Diagonal", 1000)] 0.93 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("IJV", 10)] 0.90 (5%) ✅ 1.00 (1%)
["sparse", "sparse solves", "square system (ldlt), vector rhs"] 0.95 (5%) ✅ 1.00 (1%)
["string", "==(::SubString, ::String)", "different length"] 0.92 (5%) ✅ 1.00 (1%)
["string", "==(::SubString, ::String)", "different"] 1.06 (5%) ❌ 1.00 (1%)
["string", "==(::SubString, ::String)", "equal"] 1.45 (5%) ❌ 1.00 (1%)
["string", "findfirst", "Char"] 0.91 (5%) ✅ 1.00 (1%)
["string", "readuntil", "target length 1000"] 1.16 (5%) ❌ 1.00 (1%)
["string", "readuntil", "target length 50000"] 1.23 (5%) ❌ 1.00 (1%)
["string", "repeat", "repeat str len 16"] 0.93 (5%) ✅ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(2, 2)", "(2, 2)")] 0.84 (5%) ✅ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(2, 2)", "(2,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "misc", "11899"] 1.20 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(8, 8)")] 1.09 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(16,)")] 0.88 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(4, 4)")] 1.14 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(4,)")] 1.13 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(8,)")] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float32", "(false, true)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "abs", "BigFloat", 0)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Float64", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Int8", 1)] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "BigFloat", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "Float32", 1)] 1.27 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Float64", 1)] 1.15 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Int8", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Int64", 0)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "abs", "BigFloat", 0)] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "abs", "BigFloat", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "abs", "Float32", 1)] 0.80 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "abs", "Int8", 1)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "BigFloat", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Float32", 1)] 1.27 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Float64", 1)] 1.15 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Int8", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_countequals", "Bool")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Bool", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float64", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Int8", 1)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "BigInt", 0)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum4", "BigInt", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum4", "Int8", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Float32", 0)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Float32}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("sort", "Union{Missing, Bool}", 1)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("sort", "Union{Missing, Int8}", 1)] 1.09 (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.823
Commit 551f3038d9 (2023-03-16 15:20 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.1 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     167892 s      16502 s     166398 s   35951334 s          0 s
       #2  3500 MHz    2812328 s      10736 s     185216 s   33369330 s          0 s
       #3  3900 MHz     177095 s      11031 s     144144 s   36008799 s          0 s
       #4  3900 MHz     131638 s      10386 s     148600 s   36017368 s          0 s
  Memory: 31.313323974609375 GB (21076.01953125 MB free)
  Uptime: 3.64622213e6 sec
  Load Avg:  1.15  1.03  1.01
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-14.0.6 (ORCJIT, haswell)
  Threads: 1 on 4 virtual cores