Skip to content

Latest commit

 

History

History
291 lines (269 loc) · 16.8 KB

report.md

File metadata and controls

291 lines (269 loc) · 16.8 KB

Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@e86f27fe556accb11e80d8cffb67aded754d6059 vs JuliaLang/julia@254ab94043da8f5efc65165fa9e5c8406fade0d9

Triggered By: link

Tag Predicate: ALL

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", "(\"accumulate!\", \"Float64\")"] 0.74 (15%) ✅ 1.00 (1%)
["array", "accumulate", "(\"accumulate!\", \"Int\")"] 0.58 (15%) ✅ 1.00 (1%)
["array", "accumulate", "(\"cumsum!\", \"Float64\")"] 0.79 (15%) ✅ 1.00 (1%)
["array", "accumulate", "(\"cumsum!\", \"Int\")"] 0.57 (15%) ✅ 1.00 (1%)
["array", "accumulate", "(\"cumsum\", \"Float64\")"] 0.83 (15%) ✅ 1.00 (1%)
["array", "accumulate", "(\"cumsum\", \"Int\")"] 0.72 (15%) ✅ 1.00 (1%)
["array", "any/all", "(\"all\", \"BitArray\")"] 1.17 (15%) ❌ 1.00 (1%)
["array", "comprehension", "(\"collect\", \"Array{Float64,1}\")"] 1.54 (15%) ❌ 1.00 (1%)
["array", "comprehension", "(\"collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 1.36 (15%) ❌ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"Array{Float64,1}\")"] 1.58 (15%) ❌ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 1.35 (15%) ❌ 1.00 (1%)
["array", "comprehension", "(\"comprehension_iteration\", \"Array{Float64,1}\")"] 1.22 (15%) ❌ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Float32,1}\")"] 0.62 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Float64,1}\")"] 0.69 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Int64,1} == Array{Float32,1}\")"] 0.75 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Int64,1} == Array{Float64,1}\")"] 0.72 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Int64,1} == Array{Int16,1}\")"] 0.56 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Vector{Bool}\")"] 0.59 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Float32,1}\")"] 0.68 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Float64,1}\")"] 0.68 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Int16,1}\")"] 0.59 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Int64,1} isequal Array{Float32,1}\")"] 0.75 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Int64,1} isequal Array{Float64,1}\")"] 0.70 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Int64,1} isequal Array{Int16,1}\")"] 0.56 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Array{Int64,1}\")"] 0.58 (15%) ✅ 1.00 (1%)
["array", "equality", "(\"isequal\", \"Vector{Bool}\")"] 0.55 (15%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 1000)"] 1.23 (15%) ❌ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 250)"] 1.19 (15%) ❌ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 500)"] 1.20 (15%) ❌ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 1000)"] 1.21 (15%) ❌ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 500)"] 1.16 (15%) ❌ 1.00 (1%)
["collection", "deletion", "(\"Vector\", \"Any\", \"filter!\")"] 0.73 (25%) ✅ 1.00 (1%)
["collection", "queries & updates", "(\"Dict\", \"Int\", \"pop!\", \"specified\")"] 1.28 (25%) ❌ 1.00 (1%)
["dates", "parse", "(\"DateTime\", \"DateFormat\")"] 0.97 (15%) 0.94 (1%) ✅
["dates", "parse", "(\"DateTime\", \"RFC1123Format\", \"Lowercase\")"] 0.93 (15%) 0.50 (1%) ✅
["dates", "parse", "(\"DateTime\", \"RFC1123Format\", \"Mixedcase\")"] 0.88 (15%) 0.84 (1%) ✅
["dates", "parse", "(\"DateTime\", \"RFC1123Format\", \"Titlecase\")"] 0.94 (15%) 0.50 (1%) ✅
["dates", "parse", "(\"Date\", \"DateFormat\")"] 0.98 (15%) 0.95 (1%) ✅
["find", "findall", "(\"Array{Bool,1}\", \"10-90\")"] 0.82 (15%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Bool,1}\")"] 1.26 (15%) ❌ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Float64,1}\")"] 0.81 (15%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Bool,1}\")"] 1.17 (15%) ❌ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Float64,1}\")"] 1.24 (15%) ❌ 1.00 (1%)
["linalg", "arithmetic", "(\"sqrt\", \"UnitUpperTriangular\", 1024)"] 2.43 (45%) ❌ 1.00 (1%)
["linalg", "arithmetic", "(\"sqrt\", \"UpperTriangular\", 1024)"] 2.44 (45%) ❌ 1.00 (1%)
["parallel", "remotecall", "(\"identity\", 1024)"] 0.98 (15%) 0.98 (1%) ✅
["parallel", "remotecall", "(\"identity\", 2)"] 0.99 (15%) 0.96 (1%) ✅
["parallel", "remotecall", "(\"identity\", 512)"] 1.00 (15%) 0.97 (1%) ✅
["parallel", "remotecall", "(\"identity\", 64)"] 1.00 (15%) 0.96 (1%) ✅
["problem", "grigoriadis khachiyan", "grigoriadis_khachiyan"] 1.25 (15%) ❌ 1.00 (1%)
["problem", "laplacian", "laplace_iter_sub"] 1.21 (15%) ❌ 1.00 (1%)
["problem", "laplacian", "laplace_iter_vec"] 1.24 (15%) ❌ 1.00 (1%)
["problem", "laplacian", "laplace_sparse_matvec"] 1.16 (15%) ❌ 1.00 (1%)
["problem", "ziggurat", "ziggurat"] 1.27 (15%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"'a':'z'\")"] 1.28 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"'a':'z'\")"] 1.29 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"large Vector\")"] 1.26 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"small Vector\")"] 1.26 (25%) ❌ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:2^10000)\")"] 1.37 (25%) ❌ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"Int128\", \"RangeGenerator(1:1)\")"] 1.29 (25%) ❌ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"Int128\", \"RangeGenerator(1:4294967297)\")"] 1.32 (25%) ❌ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"UInt128\", \"RangeGenerator(1:1)\")"] 1.38 (25%) ❌ 1.00 (1%)
["random", "types", "(\"rand\", \"ImplicitRNG\", \"Float64\")"] 1.31 (25%) ❌ 1.00 (1%)
["random", "types", "(\"rand\", \"MersenneTwister\", \"Complex{Float32}\")"] 1.35 (25%) ❌ 1.00 (1%)
["random", "types", "(\"randexp\", \"ImplicitRNG\", \"Float64\")"] 1.29 (25%) ❌ 1.00 (1%)
["random", "types", "(\"randexp\", \"ImplicitRNG\", \"ImplicitFloat64\")"] 1.29 (25%) ❌ 1.00 (1%)
["scalar", "acos", "(\"small\", \"positive argument\", \"Float64\")"] 0.70 (15%) ✅ 1.00 (1%)
["scalar", "arithmetic", "(\"add\", \"BigInt\", \"BigInt\")"] 1.56 (50%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"add\", \"BigInt\", \"Complex{BigInt}\")"] 1.60 (50%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"mul\", \"UInt64\", \"BigInt\")"] 1.66 (50%) ❌ 1.00 (1%)
["scalar", "atan", "(\"19/16 <= abs(x) < 39/16\", \"negative argument\", \"Float64\")"] 1.25 (15%) ❌ 1.00 (1%)
["scalar", "atan", "(\"19/16 <= abs(x) < 39/16\", \"positive argument\", \"Float64\")"] 1.25 (15%) ❌ 1.00 (1%)
["scalar", "atan", "(\"7/16 <= abs(x) < 11/16\", \"negative argument\", \"Float64\")"] 1.26 (15%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (large)\", \"y positive\", \"x negative\", \"Float32\")"] 1.47 (15%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (small)\", \"y negative\", \"x negative\", \"Float32\")"] 1.25 (15%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (small)\", \"y negative\", \"x positive\", \"Float32\")"] 1.30 (15%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float64\")"] 1.25 (15%) ❌ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float64\")"] 1.29 (15%) ❌ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 2π/4\", \"positive argument\", \"Float32\", \"sin_kernel\")"] 0.77 (15%) ✅ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 2π/4\", \"positive argument\", \"Float64\", \"sin_kernel\")"] 1.26 (15%) ❌ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 6π/4\", \"negative argument\", \"Float32\", \"sin_kernel\")"] 0.78 (15%) ✅ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 6π/4\", \"negative argument\", \"Float64\", \"sin_kernel\")"] 0.82 (15%) ✅ 1.00 (1%)
["scalar", "cosh", "(\"0 <= abs(x) < 0.00024414062f0\", \"negative argument\", \"Float32\")"] 1.17 (15%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"very large\", \"negative argument\", \"Float64\")"] 1.20 (15%) ❌ 1.00 (1%)
["scalar", "exp2", "(\"small\", \"negative argument\", \"Float64\")"] 1.16 (15%) ❌ 1.00 (1%)
["scalar", "expm1", "(\"medium\", \"negative argument\", \"Float32\")"] 0.84 (15%) ✅ 1.00 (1%)
["scalar", "intfuncs", "(\"nextpow2\", \"Int64\", \"+\")"] 0.74 (25%) ✅ 1.00 (1%)
["sparse", "arithmetic", "(\"unary minus\", (20000, 20000))"] 1.31 (30%) ❌ 1.00 (1%)
["sparse", "index", "(\"spmat\", \"row\", \"OneTo\", 1000)"] 1.31 (30%) ❌ 1.00 (1%)
["sparse", "index", "(\"spmat\", \"row\", \"logical\", 1000)"] 1.46 (30%) ❌ 1.00 (1%)
["sparse", "matmul", "(\"At_mul_B!\", \"dense 40x4000, sparse 40x40 -> dense 4000x40\")"] 1.67 (30%) ❌ 1.00 (1%)
["union", "array", "(\"perf_countnothing\", BigInt, false)"] 1.16 (15%) ❌ 1.00 (1%)
["union", "array", "(\"perf_countnothing\", BigInt, true)"] 1.16 (15%) ❌ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Float64, true)"] 1.21 (15%) ❌ 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", "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", "read"]
  • ["io", "serialization"]
  • ["linalg", "arithmetic"]
  • ["linalg", "blas"]
  • ["linalg", "factorization"]
  • ["micro"]
  • ["misc", "afoldl"]
  • ["misc", "bitshift"]
  • ["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", "transpose"]
  • ["string", "findfirst"]
  • ["string"]
  • ["string", "readuntil"]
  • ["tuple", "index"]
  • ["tuple", "linear algebra"]
  • ["tuple", "reduction"]
  • ["union", "array"]

Version Info

Primary Build

Julia Version 0.7.0-DEV.5119
Commit e86f27f (2018-05-16 19:12 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 14.04.4 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    6602399 s        248 s    1141642 s  425105233 s          4 s
       #2  3501 MHz   42671921 s          0 s     743260 s  389746882 s          4 s
       #3  3501 MHz    5829217 s       2388 s     832214 s  426706559 s          7 s
       #4  3501 MHz    5736338 s          2 s     598607 s  427289856 s          2 s
       
  Memory: 31.383651733398438 GB (4625.421875 MB free)
  Uptime: 4.338479e6 sec
  Load Avg:  1.1630859375  1.0478515625  1.05615234375
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.0 (ORCJIT, haswell)

Comparison Build

Julia Version 0.7.0-DEV.5117
Commit 254ab94 (2018-05-16 17:20 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 14.04.4 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    6728076 s        248 s    1152742 s  425854105 s          4 s
       #2  3501 MHz   43475104 s          0 s     753650 s  389822104 s          4 s
       #3  3501 MHz    5963373 s       2388 s     840790 s  427452220 s          7 s
       #4  3501 MHz    5844402 s          2 s     607084 s  428061874 s          2 s
       
  Memory: 31.383651733398438 GB (5248.953125 MB free)
  Uptime: 4.347372e6 sec
  Load Avg:  1.02783203125  1.02490234375  1.04541015625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.0 (ORCJIT, haswell)