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Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@4f17558e4c71908e8ba40d24e37bdacd5e2f2e5e

Triggered By: link

Tag Predicate: ALL

Daily Job: 2019-09-25 vs 2019-09-24

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", "bool", "boolarray_bool_load!"] 0.94 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"mean\", \"Int64\")"] 0.94 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"perf_mapreduce\", \"Int64\")"] 1.10 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"sum\", \"Int64\")"] 0.95 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", "(3, \"scal_tup_x3\")"] 0.88 (5%) ✅ 1.00 (1%)
["broadcast", "typeargs", "(\"array\", 3)"] 1.07 (5%) ❌ 1.00 (1%)
["collection", "queries & updates", "(\"BitSet\", \"Int\", \"in\", \"false\")"] 1.33 (25%) ❌ 1.00 (1%)
["dates", "parse", "(\"DateTime\", \"DateFormat\")"] 0.89 (5%) ✅ 1.00 (1%)
["dates", "parse", "(\"Date\", \"DateFormat\")"] 0.93 (5%) ✅ 1.00 (1%)
["dates", "string", "DateTime"] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", "(\"ispos\", \"Array{Float32,1}\")"] 1.06 (5%) ❌ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Int64,1}\")"] 1.07 (5%) ❌ 1.00 (1%)
["io", "array_limit", "(\"display\", \"Array{Float64,1}(100000000,)\")"] 1.06 (5%) ❌ 1.00 (1%)
["io", "array_limit", "(\"display\", \"Array{Float64,2}(10000, 10000)\")"] 0.93 (5%) ✅ 0.88 (1%) ✅
["io", "serialization", "(\"deserialize\", \"Vector{String}\")"] 0.91 (5%) ✅ 1.00 (1%)
["linalg", "arithmetic", "(\"-\", \"Matrix\", \"Matrix\", 256)"] 0.43 (45%) ✅ 1.00 (1%)
["linalg", "factorization", "(\"eigen\", \"Diagonal\", 256)"] 0.47 (45%) ✅ 1.00 (1%)
["linalg", "small exp #29116"] 1.09 (5%) ❌ 1.00 (1%)
["misc", "bitshift", "(\"UInt32\", \"UInt32\")"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "parse", "DateTime"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "repeat", "(200, 1, 24)"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "repeat", "(200, 24, 1)"] 0.93 (5%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"large BitSet\")"] 0.69 (25%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"small BitSet\")"] 0.70 (25%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"large BitSet\")"] 0.62 (25%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"large Set\")"] 1.35 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"small BitSet\")"] 0.55 (25%) ✅ 1.00 (1%)
["random", "types", "(\"randn\", \"ImplicitRNG\", \"Float64\")"] 0.74 (25%) ✅ 1.00 (1%)
["scalar", "acos", "(\"0.5 <= abs(x) < 1\", \"positive argument\", \"Float32\")"] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "acos", "(\"zero\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"rem type\", \"Int64\", \"BigInt\")"] 1.49 (40%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"rem type\", \"UInt64\", \"BigInt\")"] 1.76 (40%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"sub\", \"BigFloat\", \"Complex{BigInt}\")"] 1.51 (50%) ❌ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"positive argument\", \"Float64\")"] 0.80 (5%) ✅ 1.00 (1%)
["scalar", "asinh", "(\"zero\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asinh", "(\"zero\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "atan", "(\"11/16 <= abs(x) < 19/16\", \"negative argument\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "atan", "(\"7/16 <= abs(x) < 11/16\", \"negative argument\", \"Float64\")"] 0.80 (5%) ✅ 1.00 (1%)
["scalar", "atan", "(\"very large\", \"negative argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"very large\", \"positive argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"very small\", \"negative argument\", \"Float32\")"] 0.88 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (large)\", \"y positive\", \"x negative\", \"Float32\")"] 0.82 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (small)\", \"y negative\", \"x positive\", \"Float32\")"] 0.79 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float32\")"] 0.72 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float64\")"] 1.25 (5%) ❌ 1.00 (1%)
["scalar", "atanh", "(\"very small\", \"positive argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "cos", "(\"no reduction\", \"negative argument\", \"Float32\", \"cos_kernel\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "cos", "(\"no reduction\", \"positive argument\", \"Float64\", \"cos_kernel\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"2pow1023\", \"negative argument\", Float64)"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "exp2", "(\"2pow127\", \"negative argument\", Float32)"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"2pow35\", \"negative argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "exp2", "(\"2pow35\", \"negative argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "expm1", "(\"arg reduction II\", \"positive argument\", \"Float32\")"] 1.26 (5%) ❌ 1.00 (1%)
["scalar", "expm1", "(\"large\", \"negative argument\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (paynehanek) abs(x) > 2.0^20*π/2\", \"negative argument\", \"Float64\")"] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"small\", \"positive argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"negative argument\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", "(\"Bidiagonal\", 100)"] 1.11 (5%) ❌ 1.00 (1%)
["sparse", "constructors", "(\"Tridiagonal\", 100)"] 0.86 (5%) ✅ 1.00 (1%)
["string", "repeat", "repeat char 2"] 0.58 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (2, 2))"] 1.06 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (4, 4))"] 0.93 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (16,))"] 1.09 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (4, 4))"] 0.88 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (4,))"] 0.88 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (8,))"] 0.86 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (2, 2))"] 1.13 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (4, 4))"] 0.92 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (4,))"] 0.82 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (8,))"] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", "(\"broadcast\", *, Complex{Float64}, (true, true))"] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", "(\"broadcast\", *, Float32, (true, true))"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"broadcast\", abs, Float32, true)"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", *, Bool, (false, true))"] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", *, Bool, (true, true))"] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", abs, Float32, true)"] 0.82 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", abs, Int8, false)"] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", identity, Complex{Float64}, true)"] 0.85 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", identity, Int8, false)"] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Bool\")"] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Float32\")"] 1.13 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Bool, true)"] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Complex{Float64}, false)"] 0.76 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Float32, false)"] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Float32, true)"] 0.85 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Float64, true)"] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Int8, true)"] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Bool, true)"] 1.32 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Complex{Float64}, true)"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Float32, true)"] 1.22 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Float64, true)"] 1.15 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Bool, false)"] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Bool, true)"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Complex{Float64}, true)"] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float32, true)"] 0.81 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float64, true)"] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Int8, true)"] 0.71 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum4\", BigInt, false)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum\", Bool, true)"] 1.33 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Float64, true)"] 0.87 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Complex{Float64}}, true)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Float32}, true)"] 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 1.4.0-DEV.194
Commit 4f17558 (2019-09-23 16:31 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  101965436 s       5044 s   11848048 s  4598132849 s         28 s
       #2  3501 MHz  705028033 s        208 s   12399901 s  4001864297 s         24 s
       #3  3501 MHz   85520131 s       3254 s    7035607 s  4626810440 s         33 s
       #4  3501 MHz   80258703 s         27 s   10000626 s  4627203856 s         22 s
       
  Memory: 31.383651733398438 GB (15515.7734375 MB free)
  Uptime: 4.7228033e7 sec
  Load Avg:  0.9404296875  0.998046875  1.0400390625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, haswell)