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Benchmark Report

Job Properties

Commits: JuliaLang/julia@017b515a718add98acd329e93e93d0f543318c67 vs JuliaLang/julia@2e388e3731fcdd8d1db4c1aed5c6a39df3ef7153

Comparison Diff: link

Triggered By: link

Tag Predicate: "union" || "array"

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", "comprehension", ("comprehension_iteration", "Vector{Float64}")] 0.90 (5%) ✅ 1.00 (1%)
["array", "growth", ("append!", 8)] 1.06 (5%) ❌ 1.00 (1%)
["array", "growth", ("push_single!", 2048)] 1.05 (5%) ❌ 1.00 (1%)
["array", "growth", ("push_single!", 256)] 1.07 (5%) ❌ 1.00 (1%)
["array", "growth", ("push_single!", 8)] 1.08 (5%) ❌ 1.00 (1%)
["array", "index", ("sumelt", "BaseBenchmarks.ArrayBenchmarks.ArrayLF{Int32, 2}")] 1.80 (50%) ❌ 1.00 (1%)
["array", "reductions", ("norm1", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["broadcast", "sparse", ("(1000, 1000)", 1)] 0.92 (5%) ✅ 1.00 (1%)
["misc", "repeat", (200, 24, 1)] 1.20 (5%) ❌ 1.00 (1%)
["misc", "splatting", (3, 3, 3)] 1.06 (5%) ❌ 1.00 (1%)
["problem", "laplacian", "laplace_iter_sub"] 0.90 (5%) ✅ 1.00 (1%)
["simd", ("auto_axpy!", "Float64", 4096)] 1.66 (20%) ❌ 1.00 (1%)
["simd", ("axpy!", "Float64", 4096)] 1.66 (20%) ❌ 1.00 (1%)
["simd", ("manual_example!", "Float64", 4095)] 1.43 (20%) ❌ 1.00 (1%)
["simd", ("manual_example!", "Float64", 4096)] 1.33 (20%) ❌ 1.00 (1%)
["sparse", "constructors", ("Bidiagonal", 1000)] 0.92 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Diagonal", 100)] 0.93 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Diagonal", 1000)] 0.89 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("IJV", 1000)] 0.93 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("IV", 1000)] 0.65 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("SymTridiagonal", 100)] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("SymTridiagonal", 1000)] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Tridiagonal", 100)] 0.89 (5%) ✅ 1.00 (1%)
["sparse", "constructors", ("Tridiagonal", 1000)] 0.91 (5%) ✅ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bc", "sparse 50x500, dense 5x500 -> dense 50x5")] 0.64 (30%) ✅ 1.00 (1%)
["sparse", "matmul", ("A_mul_Bt", "sparse 50x500, dense 5x500 -> dense 50x5")] 0.66 (30%) ✅ 1.00 (1%)
["sparse", "matmul", ("Ac_mul_B", "sparse 500x500, dense 500x5 -> dense 500x5")] 0.70 (30%) ✅ 1.00 (1%)
["sparse", "matmul", ("At_mul_B!", "dense 400x400, sparse 400x400 -> dense 400x400")] 1.35 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_B!", "dense 40x400, sparse 40x400 -> dense 400x400")] 1.36 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_B!", "sparse 400x4000, dense 400x40 -> dense 4000x40")] 0.69 (30%) ✅ 1.00 (1%)
["sparse", "matmul", ("At_mul_B", "dense 500x5, sparse 500x500 -> dense 5x500")] 1.83 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_B", "dense 50x5, sparse 50x500 -> dense 5x500")] 1.98 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_B", "dense 5x5, sparse 5x500 -> dense 5x500")] 1.75 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_B", "sparse 500x500, dense 500x5 -> dense 500x5")] 1.51 (30%) ❌ 1.00 (1%)
["sparse", "matmul", ("At_mul_Bt!", "sparse 400x4000, dense 40x400 -> dense 4000x40")] 1.57 (30%) ❌ 1.00 (1%)
["sparse", "sparse matvec", "adjoint"] 1.17 (5%) ❌ 1.00 (1%)
["sparse", "sparse matvec", "non-adjoint"] 1.22 (5%) ❌ 1.00 (1%)
["sparse", "sparse solves", "square system (ldlt), matrix rhs"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Bool", "(false, false)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "ComplexF64", "(false, false)")] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float32", "(false, true)")] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "Int64", "(false, true)")] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "abs", "Int64", 0)] 1.43 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float32", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float64", 1)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Int8", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Float32", 1)] 1.24 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "all", "Float64", 1)] 0.85 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "filter", "BigFloat", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "BigFloat", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "BigInt", 0)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "BigInt", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Bool", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Bool", 1)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "ComplexF64", 1)] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Float32", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Float32", 1)] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Float64", 1)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Int64", 1)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Int8", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("collect", "filter", "Int8", 1)] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Bool", "(true, true)")] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "ComplexF64", "(false, false)")] 1.35 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "ComplexF64", "(false, true)")] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "ComplexF64", "(true, true)")] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "Int8", "(false, false)")] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Int8", "(false, true)")] 1.24 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Int8", "(true, true)")] 1.26 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "abs", "Bool", 1)] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Float32", 1)] 1.24 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "Float64", 1)] 0.85 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "BigInt", "(false, false)")] 1.14 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "BigInt", "(false, true)")] 1.14 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "BigInt", "(true, true)")] 1.18 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "ComplexF64", "(false, false)")] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float32", "(false, false)")] 1.26 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float32", "(false, true)")] 1.23 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float32", "(true, true)")] 1.20 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_countequals", "Bool")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_countequals", "ComplexF64")] 1.14 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_countequals", "Float32")] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_countequals", "Int64")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_countequals", "Int8")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigInt", 0)] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_simplecopy", "BigInt", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum", "BigInt", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "BigInt", 1)] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float64", 1)] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum4", "ComplexF64", 0)] 1.25 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "ComplexF64", 1)] 1.31 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Float32", 0)] 1.35 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Float32", 1)] 1.35 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Float64", 0)] 1.38 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Float64", 1)] 1.39 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Int64", 0)] 1.39 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Int64", 1)] 1.39 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Int8", 0)] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum4", "Int8", 1)] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "BigFloat", 0)] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "BigInt", 0)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Bool", 0)] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "ComplexF64", 0)] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, BigFloat}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Bool}", 1)] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Float32}", 1)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Float64}", 1)] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Int64}", 1)] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Int8}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, BigFloat}", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, BigInt}", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, Bool}", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, ComplexF64}", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, Float32}", 0)] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, Float64}", 0)] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, Int64}", 0)] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Nothing, Int8}", 0)] 1.16 (5%) ❌ 1.00 (1%)
["union", "array", ("sort", "Union{Missing, Bool}", 1)] 0.90 (5%) ✅ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["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", "dotop"]
  • ["broadcast", "fusion"]
  • ["broadcast", "sparse"]
  • ["broadcast", "typeargs"]
  • ["collection", "set operations"]
  • ["io", "array_limit"]
  • ["linalg", "arithmetic"]
  • ["linalg", "blas"]
  • ["linalg", "factorization"]
  • ["linalg"]
  • ["misc", "julia"]
  • ["misc", "repeat"]
  • ["misc", "splatting"]
  • ["problem", "laplacian"]
  • ["simd"]
  • ["sparse", "arithmetic"]
  • ["sparse", "constructors"]
  • ["sparse", "index"]
  • ["sparse", "matmul"]
  • ["sparse", "sparse matvec"]
  • ["sparse", "sparse solves"]
  • ["sparse", "transpose"]
  • ["union", "array"]

Version Info

Primary Build

Julia Version 1.8.0-DEV.838
Commit 017b515a71 (2021-10-29 09:47 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 20.04.3 LTS
  uname: Linux 5.4.0-1037-aws #39-Ubuntu SMP Thu Jan 14 02:56:06 UTC 2021 x86_64 x86_64
  CPU: Intel(R) Xeon(R) Platinum 8124M CPU @ 3.00GHz: 
              speed         user         nice          sys         idle          irq
       #1  3399 MHz     480605 s       5048 s      99012 s  214141647 s          0 s
       #2  3401 MHz   18353467 s       2332 s    1103090 s  195275931 s          0 s
       #3  3401 MHz     470531 s       2191 s      59015 s  214204609 s          0 s
       #4  3405 MHz     444707 s       2195 s      53917 s  214236326 s          0 s
       #5  3413 MHz     320968 s       2322 s      52206 s  214335332 s          0 s
       #6  3409 MHz     297901 s       2096 s      51086 s  214388039 s          0 s
       #7  3404 MHz     244202 s       2190 s      50863 s  214440480 s          0 s
       #8  3402 MHz     294081 s       2248 s      50790 s  214372135 s          0 s
       
  Memory: 30.362831115722656 GB (8933.5703125 MB free)
  Uptime: 2.147470902e7 sec
  Load Avg:  1.0  1.0  1.0
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake-avx512)

Comparison Build

Julia Version 1.8.0-DEV.821
Commit 2e388e3731 (2021-10-26 06:33 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 20.04.3 LTS
  uname: Linux 5.4.0-1037-aws #39-Ubuntu SMP Thu Jan 14 02:56:06 UTC 2021 x86_64 x86_64
  CPU: Intel(R) Xeon(R) Platinum 8124M CPU @ 3.00GHz: 
              speed         user         nice          sys         idle          irq
       #1  3399 MHz     480743 s       5048 s      99033 s  214197963 s          0 s
       #2  3403 MHz   18405328 s       2332 s    1106430 s  195277213 s          0 s
       #3  3411 MHz     470601 s       2191 s      59027 s  214261012 s          0 s
       #4  3409 MHz     445198 s       2195 s      53948 s  214292288 s          0 s
       #5  3412 MHz     321005 s       2322 s      52220 s  214391763 s          0 s
       #6  3405 MHz     297952 s       2096 s      51098 s  214444460 s          0 s
       #7  3403 MHz     244811 s       2190 s      50883 s  214496334 s          0 s
       #8  3400 MHz     294153 s       2248 s      50802 s  214428530 s          0 s
       
  Memory: 30.362831115722656 GB (8638.24609375 MB free)
  Uptime: 2.148035746e7 sec
  Load Avg:  1.0  1.0  1.0
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake-avx512)