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Benchmark Report

Job Properties

Commit: JuliaLang/julia@0f56da8988366dd60e170932eefca4adb890acff

Comparison Range: link

Triggered By: link

Tag Predicate: ALL

Daily Job: 2023-07-20 vs 2023-07-18

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"] 0.93 (5%) ✅ 1.00 (1%)
["array", "cat", ("catnd", 5)] 0.58 (5%) ✅ 1.00 (1%)
["array", "cat", ("hvcat", 5)] 1.06 (5%) ❌ 1.00 (1%)
["array", "cat", ("vcat", 5)] 0.86 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "UnitRange{Int64}")] 1.10 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Bool}")] 0.93 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Float64}")] 1.10 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Int64}")] 0.94 (5%) ✅ 1.00 (1%)
["array", "index", "2d"] 1.18 (5%) ❌ 1.00 (1%)
["array", "reductions", ("sumabs2", "Float64")] 1.09 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup")] 1.09 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (3, "scal_tup")] 0.92 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (5, "scal_tup")] 0.84 (5%) ✅ 1.00 (1%)
["broadcast", "sparse", ("(1000, 1000)", 1)] 0.87 (5%) ✅ 1.00 (1%)
["broadcast", "typeargs", ("tuple", 10)] 1.18 (5%) ❌ 1.00 (1%)
["collection", "optimizations", ("Set", "concrete", "Nothing")] 0.72 (25%) ✅ 1.00 (1%)
["collection", "queries & updates", ("BitSet", "Int", "length")] 0.64 (25%) ✅ 1.00 (1%)
["collection", "set operations", ("BitSet", "Int", "symdiff", "BitSet", "BitSet")] 0.72 (25%) ✅ 1.00 (1%)
["dates", "parse", "DateTime"] 1.12 (5%) ❌ 1.00 (1%)
["dates", "parse", ("Date", "DateFormat")] 0.93 (5%) ✅ 1.00 (1%)
["dates", "parse", ("DateTime", "ISODateTimeFormat")] 1.15 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Float64}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", ("BitVector", "50-50")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findnext", ("BitVector", "10-90")] 1.11 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Float32}")] 1.10 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Float64}")] 1.06 (5%) ❌ 1.00 (1%)
["find", "findprev", ("BitVector", "10-90")] 1.08 (5%) ❌ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Bool}")] 1.07 (5%) ❌ 1.00 (1%)
["inference", "abstract interpretation", "many_const_calls"] 0.95 (5%) ✅ 1.00 (1%)
["inference", "abstract interpretation", "many_invoke_calls"] 0.93 (5%) ✅ 0.99 (1%)
["inference", "abstract interpretation", "many_method_matches"] 0.94 (5%) ✅ 1.00 (1%)
["inference", "optimization", "many_local_vars"] 0.90 (5%) ✅ 1.00 (1%)
["inference", "optimization", "many_method_matches"] 0.88 (5%) ✅ 1.00 (1%)
["io", "serialization", ("deserialize", "Matrix{Float64}")] 1.22 (5%) ❌ 1.00 (1%)
["linalg", "small exp #29116"] 1.07 (5%) ❌ 1.00 (1%)
["micro", "parseint"] 1.06 (5%) ❌ 1.00 (1%)
["misc", "23042", "ComplexF32"] 0.83 (5%) ✅ 1.00 (1%)
["misc", "afoldl", "Int"] 1.19 (5%) ❌ 1.00 (1%)
["misc", "allocation elision view", "no conditional"] 0.89 (5%) ✅ 1.00 (1%)
["misc", "julia", ("parse", "function")] 1.36 (5%) ❌ 1.00 (1%)
["misc", "julia", ("parse", "nested")] 1.13 (5%) ❌ 1.00 (1%)
["misc", "perf highdim generator"] 1.06 (5%) ❌ 1.00 (1%)
["problem", "simplex", "simplex"] 1.10 (5%) ❌ 1.00 (1%)
["random", "ranges", ("RangeGenerator", "UInt128", "1:4294967295")] 1.26 (25%) ❌ 1.00 (1%)
["scalar", "acos", ("0.5 <= abs(x) < 1", "negative argument", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "acosh", ("1 <= abs(x) < 2", "positive argument", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "acosh", ("2 <= abs(x) < 2^28", "positive argument", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "arithmetic", ("div", "UInt64", "UInt64")] 1.40 (25%) ❌ 1.00 (1%)
["scalar", "asin", ("0.5 <= abs(x) < 0.975", "negative argument", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "asin", ("0.5 <= abs(x) < 0.975", "negative argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 4π/4", "negative argument", "Float32", "cos_kernel")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "exp2", ("2pow1023", "negative argument", "Float64")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 9π/4", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("large", "positive argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("medium", "negative argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("medium", "positive argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["simd", ("Cartesian", "conditional_loop!", "Int32", 2, 31)] 0.75 (20%) ✅ 1.00 (1%)
["simd", ("Cartesian", "conditional_loop!", "Int64", 3, 31)] 1.31 (20%) ❌ 1.00 (1%)
["simd", ("Cartesian", "manual_example!", "Float32", 4, 32)] 1.22 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 2, 31)] 1.22 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "inner", "Int64", 2, 32)] 1.34 (20%) ❌ 1.00 (1%)
["simd", ("Linear", "inner_aliased", "Float32", 4095)] 1.21 (20%) ❌ 1.00 (1%)
["simd", ("Linear", "inner_aliased", "Float32", 4096)] 1.28 (20%) ❌ 1.00 (1%)
["sparse", "constructors", ("Diagonal", 10)] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "sparse matvec", "adjoint"] 0.82 (5%) ✅ 1.00 (1%)
["sparse", "sparse solves", "least squares (default), matrix rhs"] 0.87 (5%) ✅ 1.00 (1%)
["sparse", "sparse solves", "least squares (default), vector rhs"] 0.88 (5%) ✅ 1.00 (1%)
["sparse", "sparse solves", "least squares (qr), matrix rhs"] 0.87 (5%) ✅ 1.00 (1%)
["sparse", "sparse solves", "least squares (qr), vector rhs"] 0.88 (5%) ✅ 1.00 (1%)
["sparse", "transpose", ("adjoint", "(20000, 10000)")] 1.40 (30%) ❌ 1.00 (1%)
["string", "repeat", "repeat char 1"] 1.06 (5%) ❌ 1.00 (1%)
["string", "repeat", "repeat char 2"] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(2, 2)", "(2, 2)")] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(2, 2)", "(2,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(4, 4)", "(4,)")] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("minimum", "(2, 2)")] 1.25 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(2, 2)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(4,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(8, 8)")] 1.06 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(2, 2)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(2,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(4,)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Bool", "(false, true)")] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float32", "(true, true)")] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float64", "(true, true)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Int8", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Bool", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float32", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Int8", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "Bool", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float64", "(false, true)")] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "Int8", "(false, true)")] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "abs", "Bool", 1)] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "abs", "Float32", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "abs", "Int8", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Bool", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Float32", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Bool", "(true, true)")] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "ComplexF64", "(false, false)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "ComplexF64", "(false, true)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "ComplexF64", "(true, true)")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float32", "(false, true)")] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float32", "(true, true)")] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float64", "(false, true)")] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float64", "(true, true)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int8", "(false, true)")] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int8", "(true, true)")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Int64", 1)] 0.85 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum", "BigFloat", 0)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum2", "BigFloat", 0)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "ComplexF64", 1)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Float32", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float64", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Int64", 1)] 1.14 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Int8", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "BigFloat", 0)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "eachindex", "Union{Nothing, BigInt}", 0)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Union{Missing, BigFloat}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Union{Nothing, BigFloat}", 0)] 1.05 (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 1.11.0-DEV.122
Commit 0f56da8988 (2023-07-19 09:09 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.2 LTS
  uname: Linux 5.15.0-76-generic #83-Ubuntu SMP Thu Jun 15 19:16:32 UTC 2023 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1   800 MHz      30497 s          2 s      19562 s   12321585 s          0 s
       #2  3520 MHz     841231 s         16 s      38082 s   11492613 s          0 s
       #3   800 MHz      29981 s         14 s      21777 s   12305752 s          0 s
       #4   800 MHz      23589 s         16 s      22488 s   12310394 s          0 s
       #5   800 MHz      23078 s         21 s      24691 s   12271570 s          0 s
       #6   800 MHz      25835 s         10 s      24201 s   12314866 s          0 s
       #7  2500 MHz      28498 s          3 s      30410 s   12311039 s          0 s
       #8   800 MHz      24577 s          9 s      19575 s   12322416 s          0 s
  Memory: 31.301593780517578 GB (26083.51953125 MB free)
  Uptime: 1.23844457e6 sec
  Load Avg:  1.0  1.01  1.0
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, haswell)
  Threads: 1 on 8 virtual cores