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Benchmark Report

Job Properties

Commits: JuliaLang/julia@167c219ab98512ae09121ce5f19b29d7b044dc54 vs JuliaLang/julia@a734ae4e4aa7fc0aa7dba8d91060fd9462411536

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
["alloc", "grow_array"] 1.05 (5%) ❌ 1.00 (1%)
["array", "accumulate", ("cumsum!", "Float64", "dim1")] 0.92 (5%) ✅ 1.00 (1%)
["array", "accumulate", ("cumsum!", "Float64", "dim2")] 0.92 (5%) ✅ 1.00 (1%)
["array", "accumulate", ("cumsum!", "Int")] 1.22 (5%) ❌ 1.00 (1%)
["array", "cat", ("catnd", 5)] 1.09 (5%) ❌ 1.00 (1%)
["array", "equality", ("==", "UnitRange{Int64}")] 0.91 (5%) ✅ 1.00 (1%)
["array", "equality", ("==", "Vector{Int64}")] 1.06 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "UnitRange{Int64}")] 1.22 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal UnitRange{Int64}")] 1.11 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Int64}")] 1.07 (5%) ❌ 1.00 (1%)
["array", "reductions", ("sum", "Float64")] 1.05 (5%) ❌ 1.00 (1%)
["array", "reductions", ("sumabs2", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["array", "reverse", "rev_load_fast!"] 1.08 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 4)] 0.94 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup")] 4.51 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "tup_tup")] 1.08 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", ("tuple", 10)] 1.11 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", ("tuple", 5)] 0.94 (5%) ✅ 1.00 (1%)
["collection", "deletion", ("Dict", "Any", "pop!")] 1.28 (25%) ❌ 1.00 (1%)
["collection", "deletion", ("Set", "Int", "filter!")] 0.55 (25%) ✅ 1.00 (1%)
["collection", "set operations", ("Set", "Int", "⊆", "BitSet")] 1.59 (25%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Bool}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Float32}")] 1.05 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Float64}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{UInt8}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Bool}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Float32}")] 1.14 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Float64}")] 1.13 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Int64}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Int8}")] 1.13 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{UInt64}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{Bool}")] 1.11 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{Float32}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{Float64}")] 1.10 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.99", "Vector{Bool}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.99", "Vector{Float32}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.99", "Vector{Float64}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "10-90")] 1.12 (5%) ❌ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "50-50")] 1.14 (5%) ❌ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "90-10")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Bool}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Int8}")] 1.05 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{UInt64}")] 1.13 (5%) ❌ 1.00 (1%)
["inference", "abstract interpretation", "abstract_call_gf_by_type"] 1.10 (5%) ❌ 1.14 (1%) ❌
["inference", "abstract interpretation", "construct_ssa!"] 1.12 (5%) ❌ 1.13 (1%) ❌
["inference", "abstract interpretation", "domsort_ssa!"] 1.13 (5%) ❌ 1.13 (1%) ❌
["inference", "abstract interpretation", "println(::QuoteNode)"] 1.14 (5%) ❌ 1.14 (1%) ❌
["inference", "abstract interpretation", "rand(Float64)"] 1.12 (5%) ❌ 1.18 (1%) ❌
["inference", "abstract interpretation", "sin(42)"] 1.14 (5%) ❌ 1.13 (1%) ❌
["inference", "abstract_call_gf_by_type"] 1.03 (5%) 1.04 (1%) ❌
["inference", "construct_ssa!"] 1.03 (5%) 1.03 (1%) ❌
["inference", "domsort_ssa!"] 1.04 (5%) 1.02 (1%) ❌
["inference", "println(::QuoteNode)"] 1.05 (5%) ❌ 1.03 (1%) ❌
["inference", "rand(Float64)"] 1.06 (5%) ❌ 1.04 (1%) ❌
["inference", "sin(42)"] 1.07 (5%) ❌ 1.03 (1%) ❌
["misc", "23042", "Float64"] 0.88 (5%) ✅ 1.00 (1%)
["misc", "foldl", "foldl(+, filter(...))"] 0.86 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000)"] 1.09 (5%) ❌ 1.00 (1%)
["problem", "simplex", "simplex"] 0.91 (5%) ✅ 1.00 (1%)
["random", "ranges", ("RangeGenerator", "Int128", "1:4294967295")] 1.39 (25%) ❌ 1.00 (1%)
["shootout", "binary_trees"] 1.05 (5%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 2, 63)] 1.66 (20%) ❌ 1.00 (1%)
["sparse", "constructors", ("IJV", 1000)] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("IV", 10)] 1.11 (5%) ❌ 1.00 (1%)
["sparse", "constructors", ("SymTridiagonal", 100)] 1.11 (5%) ❌ 1.00 (1%)
["sparse", "constructors", ("Tridiagonal", 100)] 1.13 (5%) ❌ 1.00 (1%)
["string", "==(::SubString, ::String)", "different length"] 1.09 (5%) ❌ 1.00 (1%)
["string", "readuntil", "target length 1"] 1.14 (5%) ❌ 1.00 (1%)
["string", "repeat", "repeat str len 16"] 1.06 (5%) ❌ 1.00 (1%)
["tuple", "index", ("sumelt", "TupleWrapper", 30, "Float32")] 1.42 (40%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(4, 4)", "(4, 4)")] 1.64 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(8, 8)", "(8, 8)")] 1.21 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(2, 2)", "(2,)")] 0.88 (5%) ✅ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(8, 8)", "(8,)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "misc", "longtuple"] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(2,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(16,)")] 0.91 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(8,)")] 1.25 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(2, 2)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(4,)")] 1.60 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "BigFloat", "(false, false)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "Float32", 1)] 0.82 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Int8", 0)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Bool", 0)] 1.06 (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"]
  • ["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", "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 1.9.0-DEV.539
Commit 167c219ab9 (2022-05-11 09:56 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 20.04.3 LTS
  uname: Linux 5.4.0-94-generic #106-Ubuntu SMP Thu Jan 6 23:58:14 UTC 2022 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1  3768 MHz     365676 s        968 s      68083 s  101223062 s          0 s
       #2  3782 MHz    6184754 s        668 s     263195 s   95279509 s          0 s
       #3  3578 MHz     384725 s        640 s      53556 s  101279198 s          0 s
       #4  3521 MHz     266534 s        734 s      51838 s  101022492 s          0 s
  Memory: 31.32097625732422 GB (15789.27734375 MB free)
  Uptime: 1.018159366e7 sec
  Load Avg:  1.0  1.0  1.0
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, haswell)
  Threads: 1 on 4 virtual cores

Comparison Build

Julia Version 1.9.0-DEV.535
Commit a734ae4e4a (2022-05-11 08:48 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 20.04.3 LTS
  uname: Linux 5.4.0-94-generic #106-Ubuntu SMP Thu Jan 6 23:58:14 UTC 2022 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1  3568 MHz     366309 s        968 s      68249 s  101323957 s          0 s
       #2  3758 MHz    6280859 s        668 s     267406 s   95281070 s          0 s
       #3  3560 MHz     385651 s        640 s      53587 s  101380094 s          0 s
       #4  3530 MHz     266706 s        734 s      51852 s  101123967 s          0 s
  Memory: 31.32097625732422 GB (15500.796875 MB free)
  Uptime: 1.019178163e7 sec
  Load Avg:  1.0  1.0  1.0
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, haswell)
  Threads: 1 on 4 virtual cores