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Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@eddcbd7585152c1e404ed0481ffe44c61d504e77

Triggered By: link

Tag Predicate: ALL

Daily Job: 2018-12-19 vs 2018-12-18

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
["array", "accumulate", "(\"cumsum!\", \"Float64\", \"dim1\")"] 0.94 (5%) ✅ 1.00 (1%)
["array", "cat", "(\"catnd\", 5)"] 1.06 (5%) ❌ 1.00 (1%)
["array", "cat", "(\"hcat\", 5)"] 0.85 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"collect\", \"Array{Float64,1}\")"] 0.69 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 0.78 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"Array{Float64,1}\")"] 0.72 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 0.78 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_iteration\", \"Array{Float64,1}\")"] 0.86 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_iteration\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 0.90 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"append!\", 2048)"] 0.95 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"append!\", 256)"] 1.09 (5%) ❌ 1.00 (1%)
["array", "growth", "(\"prerend!\", 256)"] 1.17 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"BaseBenchmarks.ArrayBenchmarks.perf_mapreduce\", \"Int64\")"] 1.13 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"Statistics.mean\", \"Int64\")"] 1.07 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"maxabs\", \"Float64\")"] 0.45 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"maxabs\", \"Int64\")"] 0.79 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"sum\", \"Int64\")"] 1.06 (5%) ❌ 1.00 (1%)
["array", "reverse", "rev_load_fast!"] 0.94 (5%) ✅ 1.00 (1%)
["array", "reverse", "rev_load_slow!"] 0.91 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 1000)"] 0.88 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 250)"] 0.88 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 500)"] 0.87 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 1000)"] 0.90 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 250)"] 0.92 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 500)"] 0.89 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", "(3, \"scal_tup_x3\")"] 0.93 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", "(5, \"scal_tup_x3\")"] 1.42 (5%) ❌ 1.00 (1%)
["collection", "iteration", "(\"Dict\", \"Any\", \"iterate second\")"] 0.71 (25%) ✅ 1.00 (1%)
["collection", "iteration", "(\"IdDict\", \"String\", \"iterate\")"] 1.94 (25%) ❌ 1.00 (1%)
["collection", "set operations", "(\"BitSet\", \"Int\", \"intersect!\", \"big\")"] 1.35 (25%) ❌ 1.00 (1%)
["dates", "parse", "(\"DateTime\", \"DateFormat\")"] 0.93 (5%) ✅ 1.00 (1%)
["dates", "string", "DateTime"] 1.06 (5%) ❌ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Float64,1}\")"] 0.92 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"BitArray{1}\", \"50-50\")"] 0.93 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Float64,1}\")"] 1.05 (5%) ❌ 1.00 (1%)
["misc", "18129"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "23042", "Complex{Float32}"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "allocation elision view", "conditional"] 0.89 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"Int\", \"UInt\")"] 0.94 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"UInt32\", \"UInt32\")"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "bitshift", "(\"UInt\", \"UInt\")"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1, 1:1)"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000, 1:1000)"] 0.89 (5%) ✅ 1.00 (1%)
["problem", "fem", "sparse_fem"] 0.94 (5%) ✅ 1.00 (1%)
["problem", "go", "go_game"] 0.95 (5%) ✅ 1.00 (1%)
["problem", "grigoriadis khachiyan", "grigoriadis_khachiyan"] 0.85 (5%) ✅ 1.00 (1%)
["problem", "laplacian", "laplace_iter_sub"] 0.83 (5%) ✅ 1.00 (1%)
["problem", "laplacian", "laplace_iter_vec"] 0.81 (5%) ✅ 1.00 (1%)
["problem", "simplex", "simplex"] 1.10 (5%) ❌ 1.00 (1%)
["problem", "stockcorr", "stockcorr"] 0.93 (5%) ✅ 1.00 (1%)
["problem", "ziggurat", "ziggurat"] 0.84 (5%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"'a':'z'\")"] 0.67 (25%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"small Dict\")"] 1.33 (25%) ❌ 1.00 (1%)
["scalar", "acos", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float32\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "acos", "(\"small\", \"negative argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "acos", "(\"small\", \"negative argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "acos", "(\"small\", \"positive argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "acos", "(\"small\", \"positive argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"positive argument\", \"Float32\")"] 0.89 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"positive argument\", \"Float64\")"] 0.80 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"abs(x) < 0.5\", \"negative argument\", \"Float32\")"] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"small\", \"negative argument\", \"Float32\")"] 0.88 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"small\", \"positive argument\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"zero\", \"Float32\")"] 0.82 (5%) ✅ 1.00 (1%)
["scalar", "asinh", "(\"zero\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "atan", "(\"0 <= abs(x) < 7/16\", \"negative argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"19/16 <= abs(x) < 39/16\", \"positive argument\", \"Float64\")"] 1.22 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"7/16 <= abs(x) < 11/16\", \"positive argument\", \"Float32\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"zero\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float32\")"] 1.40 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float64\")"] 0.82 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float64\")"] 1.25 (5%) ❌ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"positive argument\", \"Float32\")"] 1.25 (5%) ❌ 1.00 (1%)
["scalar", "atanh", "(\"one\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atanh", "(\"very small\", \"negative argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atanh", "(\"zero\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "cos", "(\"no reduction\", \"negative argument\", \"Float64\", \"cos_kernel\")"] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "cos", "(\"no reduction\", \"positive argument\", \"Float64\", \"cos_kernel\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"0 <= abs(x) < 2.7755602085408512e-17\", \"negative argument\", \"Float64\")"] 1.10 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"0 <= abs(x) < 2.7755602085408512e-17\", \"positive argument\", \"Float64\")"] 1.10 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"9f0 <= abs(x) < 88.72283f0\", \"negative argument\", \"Float32\")"] 1.22 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"9f0 <= abs(x) < 88.72283f0\", \"positive argument\", \"Float32\")"] 1.22 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"very large\", \"negative argument\", \"Float64\")"] 1.14 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"very large\", \"positive argument\", \"Float64\")"] 1.14 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"very small\", \"negative argument\", \"Float64\")"] 1.15 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"very small\", \"positive argument\", \"Float64\")"] 1.10 (5%) ❌ 1.00 (1%)
["scalar", "exp2", "(\"2pow35\", \"negative argument\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "expm1", "(\"arg reduction I\", \"negative argument\", \"Float32\")"] 0.82 (5%) ✅ 1.00 (1%)
["scalar", "expm1", "(\"one\", \"Float32\")"] 1.22 (5%) ❌ 1.00 (1%)
["scalar", "rem_pio2", "(\"argument reduction (paynehanek) abs(x) > 2.0^20*π/2\", \"positive argument\", \"Float64\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "sin", "(\"argument reduction (paynehanek) abs(x) > 2.0^20*π/2\", \"negative argument\", \"Float64\", \"cos_kernel\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "sin", "(\"no reduction\", \"negative argument\", \"Float32\", \"sin_kernel\")"] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "sin", "(\"no reduction\", \"positive argument\", \"Float32\", \"sin_kernel\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (paynehanek) abs(x) > 2.0^20*π/2\", \"negative argument\", \"Float32\")"] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (paynehanek) abs(x) > 2.0^20*π/2\", \"positive argument\", \"Float32\")"] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (paynehanek) abs(x) > 2.0^20*π/2\", \"positive argument\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"small\", \"positive argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["sparse", "constructors", "(\"Diagonal\", 10)"] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "sparse matvec", "adjoint"] 0.88 (5%) ✅ 1.00 (1%)
["sparse", "sparse matvec", "non-adjoint"] 0.89 (5%) ✅ 1.00 (1%)
["string", "repeat", "repeat str len 16"] 1.11 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (16,))"] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (2, 2))"] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (16, 16))"] 0.82 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (2,))"] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (8, 8))"] 1.29 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (8,))"] 1.16 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (4, 4))"] 0.92 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (8,))"] 0.84 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", *, Bool, (false, true))"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", *, Float32, (false, false))"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", abs, Float32, true)"] 1.17 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", identity, BigFloat, false)"] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", identity, BigFloat, true)"] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", identity, Int8, true)"] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Int64\")"] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", BigFloat, false)"] 0.87 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", BigFloat, true)"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Bool, true)"] 1.19 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Float32, true)"] 0.87 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Int8, true)"] 0.80 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Float64, true)"] 1.22 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float32, true)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float64, true)"] 1.23 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Int8, true)"] 0.70 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum\", Bool, true)"] 1.33 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Float32, true)"] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum\", Float64, true)"] 1.21 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Complex{Float64}}, true)"] 1.21 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Float32}, true)"] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Float64}, true)"] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", "(\"sort\", Union{Nothing, Int64}, false)"] 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"]
  • ["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"]
  • ["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", "issue 12165"]
  • ["misc", "iterators"]
  • ["misc", "julia"]
  • ["misc", "parse"]
  • ["misc", "repeat"]
  • ["misc", "splatting"]
  • ["parallel", "remotecall"]
  • ["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", "findfirst"]
  • ["string"]
  • ["string", "readuntil"]
  • ["string", "repeat"]
  • ["tuple", "index"]
  • ["tuple", "linear algebra"]
  • ["tuple", "misc"]
  • ["tuple", "reduction"]
  • ["union", "array"]

Version Info

Primary Build

Julia Version 1.2.0-DEV.35
Commit eddcbd7 (2018-12-18 21:59 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 14.04.5 LTS
  uname: Linux 3.13.0-85-generic #129-Ubuntu SMP Thu Mar 17 20:50:15 UTC 2016 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1  3501 MHz   67224962 s       5010 s    7424363 s  2223488642 s         22 s
       #2  3501 MHz  378901207 s        203 s    6178105 s  1916916614 s         18 s
       #3  3501 MHz   51217857 s       3218 s    4325561 s  2246372623 s         26 s
       #4  3501 MHz   47823561 s          0 s    5538975 s  2248061415 s         16 s
       
  Memory: 31.383651733398438 GB (5392.73046875 MB free)
  Uptime: 2.3038941e7 sec
  Load Avg:  0.97900390625  1.0126953125  1.04345703125
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, haswell)