Skip to content

Latest commit

 

History

History
288 lines (269 loc) · 16.1 KB

report.md

File metadata and controls

288 lines (269 loc) · 16.1 KB
Raw

Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@9a8b2fd72b675bb8a5bf0322943ee9451787b86a

Triggered By: link

Tag Predicate: ALL

Daily Job: 2019-08-29 vs 2019-08-28

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\")"] 1.06 (5%) ❌ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Int64,1} isequal Array{Int64,1}\")"] 1.07 (5%) ❌ 1.00 (1%)
["array", "growth", "(\"prerend!\", 256)"] 0.95 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"push_multiple!\", 8)"] 1.11 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"mean\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"perf_mapreduce\", \"Int64\")"] 1.13 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"perf_reduce\", \"Int64\")"] 1.08 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"sum\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"sumabs\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", "(10, \"scal_tup_x3\")"] 1.17 (5%) ❌ 1.00 (1%)
["broadcast", "mix_scalar_tuple", "(3, \"scal_tup_x3\")"] 0.94 (5%) ✅ 1.00 (1%)
["collection", "iteration", "(\"IdDict\", \"String\", \"iterate\")"] 1.33 (25%) ❌ 1.00 (1%)
["collection", "iteration", "(\"Vector\", \"String\", \"iterate\")"] 1.28 (25%) ❌ 1.00 (1%)
["dates", "parse", "(\"DateTime\", \"DateFormat\")"] 0.94 (5%) ✅ 1.00 (1%)
["dates", "parse", "(\"DateTime\", \"ISODateTimeFormat\")"] 1.34 (5%) ❌ 1.00 (1%)
["dates", "parse", "(\"Date\", \"DateFormat\")"] 0.94 (5%) ✅ 1.00 (1%)
["find", "findall", "(\"BitArray{1}\", \"10-90\")"] 0.92 (5%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Float64,1}\")"] 0.93 (5%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{UInt64,1}\")"] 1.06 (5%) ❌ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Float32,1}\")"] 0.93 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Float64,1}\")"] 0.94 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Int64,1}\")"] 0.94 (5%) ✅ 1.00 (1%)
["io", "array_limit", "(\"display\", \"Array{Float64,2}(10000, 10000)\")"] 1.03 (5%) 1.04 (1%) ❌
["io", "serialization", "(\"deserialize\", \"Vector{String}\")"] 1.08 (5%) ❌ 1.00 (1%)
["io", "skipchars"] 1.00 (5%) 1.11 (1%) ❌
["linalg", "arithmetic", "(\"-\", \"Matrix\", \"Matrix\", 256)"] 2.23 (45%) ❌ 1.00 (1%)
["linalg", "factorization", "(\"eigen\", \"Diagonal\", 256)"] 2.15 (45%) ❌ 1.00 (1%)
["misc", "23042", "Float64"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "fastmath many args"] 0.65 (5%) ✅ 1.00 (1%)
["problem", "simplex", "simplex"] 0.91 (5%) ✅ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:170141183460469231731687303715884105728)\")"] 0.74 (25%) ✅ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:2^10000)\")"] 0.74 (25%) ✅ 1.00 (1%)
["random", "types", "(\"randn\", \"ImplicitRNG\", \"Float64\")"] 0.74 (25%) ✅ 1.00 (1%)
["scalar", "acosh", "(\"very large\", \"positive argument\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "arithmetic", "(\"add\", \"BigInt\", \"BigInt\")"] 1.54 (50%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"mul\", \"UInt64\", \"BigInt\")"] 1.64 (50%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"sub\", \"Complex{BigFloat}\", \"BigInt\")"] 1.53 (50%) ❌ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"positive argument\", \"Float32\")"] 1.12 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"0.975 <= abs(x) < 1.0\", \"negative argument\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"0.975 <= abs(x) < 1.0\", \"positive argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"abs(x) < 0.5\", \"positive argument\", \"Float32\")"] 1.15 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"small\", \"negative argument\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"small\", \"positive argument\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"zero\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"19/16 <= abs(x) < 39/16\", \"negative argument\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "atan", "(\"39/16 <= abs(x) < 2^66\", \"positive argument\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "atan", "(\"very small\", \"negative argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"very small\", \"positive argument\", \"Float64\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (large)\", \"y negative\", \"x negative\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (large)\", \"y positive\", \"x positive\", \"Float32\")"] 0.78 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float32\")"] 1.43 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"y infinite\", \"y positive\", \"x finite\", \"x positive\", \"Float64\")"] 1.38 (5%) ❌ 1.00 (1%)
["scalar", "cbrt", "(\"large\", \"negative argument\", \"Float32\")"] 0.87 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"2pow127\", \"positive argument\", Float32)"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"2pow35\", \"negative argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "exp2", "(\"zero\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "expm1", "(\"arg reduction II\", \"negative argument\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", "(\"argument reduction (easy) abs(x) < 2π/4\", \"negative argument\", \"Float64\", \"cos_kernel\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "sin", "(\"argument reduction (easy) abs(x) < 8π/4\", \"negative argument\", \"Float64\", \"sin_kernel\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sin", "(\"no reduction\", \"positive argument\", \"Float64\", \"sin_kernel\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (easy) abs(x) < 7π/4\", \"positive argument\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"small\", \"positive argument\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"negative argument\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"positive argument\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"positive argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"zero\", \"Float32\")"] 1.06 (5%) ❌ 1.00 (1%)
["shootout", "mandelbrot"] 1.00 (5%) 1.03 (1%) ❌
["sparse", "constructors", "(\"Bidiagonal\", 100)"] 0.88 (5%) ✅ 1.00 (1%)
["sparse", "constructors", "(\"IJV\", 100)"] 1.06 (5%) ❌ 1.00 (1%)
["sparse", "constructors", "(\"IJV\", 1000)"] 1.06 (5%) ❌ 1.00 (1%)
["sparse", "constructors", "(\"IV\", 1000)"] 0.93 (5%) ✅ 1.00 (1%)
["sparse", "constructors", "(\"Tridiagonal\", 100)"] 0.89 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (2, 2))"] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (4, 4))"] 0.93 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (2, 2))"] 1.05 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (4, 4))"] 1.14 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (16,))"] 1.09 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (2, 2))"] 1.06 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (4,))"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"broadcast\", identity, Bool, true)"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", *, Bool, (false, true))"] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", abs, Float32, true)"] 1.19 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", abs, Int64, true)"] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Int64\")"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Bool, true)"] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Float64, true)"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Int64, false)"] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Float32, true)"] 0.84 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Int8, false)"] 1.23 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Bool, true)"] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Complex{Float64}, true)"] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float64, true)"] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Int8, true)"] 0.70 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum4\", Complex{Float64}, true)"] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Bool, true)"] 1.32 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Float32, true)"] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Bool}, true)"] 1.27 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Float64}, true)"] 1.10 (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.70
Commit 9a8b2fd (2019-08-28 19:26 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   98796128 s       5042 s   11441876 s  4368908008 s         28 s
       #2  3501 MHz  670845258 s        208 s   11577348 s  3803819005 s         24 s
       #3  3501 MHz   82274984 s       3248 s    6806920 s  4397139645 s         32 s
       #4  3501 MHz   77170707 s         24 s    9631440 s  4397633070 s         22 s
       
  Memory: 31.383651733398438 GB (14570.3515625 MB free)
  Uptime: 4.4895276e7 sec
  Load Avg:  0.9404296875  0.998046875  1.0400390625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, haswell)