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Benchmark Report

Job Properties

Commits: jakobnissen/julia@c74831236b721a5c2614408e583ad808fe93334a vs JuliaLang/julia@b81a20cf04165df531bdbf271f35f6982e739519

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", ("cumsum!", "Float64", "dim1")] 0.92 (5%) ✅ 1.00 (1%)
["array", "accumulate", ("cumsum!", "Float64", "dim2")] 0.93 (5%) ✅ 1.00 (1%)
["array", "comprehension", ("collect", "StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}")] 0.55 (5%) ✅ 1.00 (1%)
["array", "comprehension", ("collect", "Vector{Float64}")] 0.23 (5%) ✅ 1.00 (1%)
["array", "comprehension", ("comprehension_collect", "StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}")] 0.55 (5%) ✅ 1.00 (1%)
["array", "comprehension", ("comprehension_collect", "Vector{Float64}")] 0.39 (5%) ✅ 1.00 (1%)
["array", "comprehension", ("comprehension_iteration", "StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}")] 0.81 (5%) ✅ 1.00 (1%)
["array", "comprehension", ("comprehension_iteration", "Vector{Float64}")] 0.69 (5%) ✅ 1.00 (1%)
["array", "equality", ("==", "BitArray")] 0.92 (5%) ✅ 1.00 (1%)
["array", "index", "2d"] 1.22 (5%) ❌ 1.00 (1%)
["array", "reductions", ("perf_reduce", "Int64")] 1.05 (5%) ❌ 1.00 (1%)
["broadcast", "dotop", ("Float64", "(1000, 1000)", 2)] 1.07 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "tup_tup")] 1.11 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", ("array", 10)] 0.94 (5%) ✅ 1.00 (1%)
["broadcast", "typeargs", ("tuple", 10)] 0.83 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("Date", "Day")] 0.90 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Day")] 0.90 (5%) ✅ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Hour")] 1.11 (5%) ❌ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Millisecond")] 1.11 (5%) ❌ 1.00 (1%)
["dates", "arithmetic", ("DateTime", "Second")] 1.09 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{Bool}")] 1.18 (5%) ❌ 0.48 (1%) ✅
["find", "findall", ("> q0.5", "Vector{Float32}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.5", "Vector{UInt8}")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Bool}")] 0.35 (5%) ✅ 0.02 (1%) ✅
["find", "findall", ("> q0.8", "Vector{Float32}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Float64}")] 1.09 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{Int8}")] 1.07 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.8", "Vector{UInt64}")] 1.08 (5%) ❌ 1.00 (1%)
["find", "findall", ("> q0.95", "Vector{Bool}")] 0.35 (5%) ✅ 0.02 (1%) ✅
["find", "findall", ("> q0.99", "Vector{Bool}")] 0.35 (5%) ✅ 0.02 (1%) ✅
["find", "findall", ("> q0.99", "Vector{Int8}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", ("BitVector", "50-50")] 0.92 (5%) ✅ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "10-90")] 1.18 (5%) ❌ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "50-50")] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", ("Vector{Bool}", "90-10")] 0.89 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Bool}")] 0.74 (5%) ✅ 0.48 (1%) ✅
["find", "findall", ("ispos", "Vector{Float32}")] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Float64}")] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{Int8}")] 0.90 (5%) ✅ 1.00 (1%)
["find", "findall", ("ispos", "Vector{UInt8}")] 0.92 (5%) ✅ 1.00 (1%)
["find", "findnext", ("Vector{Bool}", "50-50")] 1.08 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Float32}")] 1.10 (5%) ❌ 1.00 (1%)
["find", "findnext", ("ispos", "Vector{Int8}")] 1.24 (5%) ❌ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{Bool}")] 0.86 (5%) ✅ 1.00 (1%)
["find", "findprev", ("ispos", "Vector{UInt8}")] 0.89 (5%) ✅ 1.00 (1%)
["inference", "optimization", "println(::QuoteNode)"] 0.94 (5%) ✅ 1.00 (1%)
["linalg", "small exp #29116"] 1.09 (5%) ❌ 1.00 (1%)
["micro", "printfd"] 0.82 (5%) ✅ 1.00 (1%)
["misc", "afoldl", "Float64"] 1.33 (5%) ❌ 1.00 (1%)
["misc", "allocation elision view", "conditional"] 0.85 (5%) ✅ 1.00 (1%)
["misc", "allocation elision view", "no conditional"] 0.85 (5%) ✅ 1.00 (1%)
["misc", "fastmath many args"] 0.90 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000, 1:1000)"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "repeat", (200, 1, 24)] 1.05 (5%) ❌ 1.00 (1%)
["simd", ("Cartesian", "axpy!", "Int32", 2, 64)] 0.56 (20%) ✅ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 2, 31)] 1.50 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 4, 31)] 1.51 (20%) ❌ 1.00 (1%)
["sparse", "constructors", ("Bidiagonal", 1000)] 1.05 (5%) ❌ 1.00 (1%)
["sparse", "constructors", ("IJV", 10)] 0.91 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("IV", 10)] 0.87 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("SymTridiagonal", 100)] 0.90 (5%) ✅ 1.00 (1%)
["sparse", "index", ("spvec", "logical", 10000)] 0.41 (30%) ✅ 1.00 (1%)
["sparse", "index", ("spvec", "logical", 100000)] 0.37 (30%) ✅ 1.00 (1%)
["string", "==(::AbstractString, ::AbstractString)", "different"] 1.06 (5%) ❌ 1.00 (1%)
["string", "==(::SubString, ::String)", "different length"] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(4, 4)", "(4, 4)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matmat", "(8, 8)", "(8, 8)")] 1.18 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(16, 16)", "(16,)")] 1.90 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(2, 2)", "(2,)")] 1.27 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(8, 8)", "(8,)")] 0.80 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(8,)")] 1.10 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sumabs", "(4,)")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "Bool", "(true, true)")] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Bool", 1)] 0.84 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Int8", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Bool", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "Int8", 1)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "BigFloat", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Bool", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Int8", 1)] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum", "BigFloat", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "BigFloat", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "Float32", 1)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum", "Float64", 1)] 0.87 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum2", "Float32", 1)] 1.41 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Bool", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "ComplexF64", 1)] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum3", "Float32", 1)] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Int8", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "perf_sumskipmissing", "Int8", 0)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "BigFloat", 0)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Bool", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Int8", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Union{Nothing, BigInt}", 0)] 0.92 (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.629
Commit c74831236b (2022-05-20 06:29 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  3776 MHz     390979 s       1038 s      72942 s  108834416 s          0 s
       #2  3521 MHz    6819525 s        732 s     293221 s  102261179 s          0 s
       #3  3505 MHz     413576 s        687 s      57409 s  108892174 s          0 s
       #4  3504 MHz     289424 s        788 s      55617 s  108620298 s          0 s
  Memory: 31.32097625732422 GB (15821.3515625 MB free)
  Uptime: 1.094682735e7 sec
  Load Avg:  1.24  1.06  1.02
  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.620
Commit b81a20cf04 (2022-05-20 01:43 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  3756 MHz     391641 s       1038 s      73140 s  108935475 s          0 s
       #2  3561 MHz    6915953 s        732 s     297482 s  102262712 s          0 s
       #3  3564 MHz     414460 s        687 s      57440 s  108993452 s          0 s
       #4  3577 MHz     289627 s        788 s      55632 s  108722098 s          0 s
  Memory: 31.32097625732422 GB (16153.6328125 MB free)
  Uptime: 1.095704997e7 sec
  Load Avg:  1.16  1.08  1.02
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, haswell)
  Threads: 1 on 4 virtual cores