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Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@e9a5fbbe170f8c52174830f4a08bdb196ce5e822 vs JuliaLang/julia@feb9260680fd5f271de9e188e66e043ff257360f

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", "comprehension", "(\"comprehension_collect\", \"Array{Float64,1}\")"] 1.28 (15%) ❌ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 1.16 (15%) ❌ 1.00 (1%)
["broadcast", "dotop", "(\"Float64\", (1000, 1000), 2)"] 0.75 (15%) ✅ 1.00 (1%)
["broadcast", "typeargs", "(\"tuple\", 10)"] 1.25 (15%) ❌ 1.00 (1%)
["collection", "iteration", "(\"IdDict\", \"Any\", \"next\")"] 0.70 (25%) ✅ 1.00 (1%)
["collection", "set operations", "(\"Vector\", \"Int\", \"⊆\", \"Set\")"] 0.55 (25%) ✅ 1.00 (1%)
["dates", "query", "(\"dayofweekofmonth\", \"DateTime\")"] 1.34 (25%) ❌ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Float32,1}\")"] 0.83 (15%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Float64,1}\")"] 1.33 (15%) ❌ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Bool,1}\")"] 0.79 (15%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Float64,1}\")"] 1.18 (15%) ❌ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Int64,1}\")"] 1.29 (15%) ❌ 1.00 (1%)
["problem", "laplacian", "laplace_iter_vec"] 0.84 (15%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"large Dict\")"] 0.64 (25%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"small Dict\")"] 1.34 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"large Dict\")"] 0.70 (25%) ✅ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:2^10000)\")"] 1.31 (25%) ❌ 1.00 (1%)
["scalar", "acos", "(\"abs(x) < 0.5\", \"negative argument\", \"Float32\")"] 1.18 (15%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"mul\", \"UInt64\", \"Complex{UInt64}\")"] 1.64 (50%) ❌ 1.00 (1%)
["scalar", "atan", "(\"19/16 <= abs(x) < 39/16\", \"negative argument\", \"Float64\")"] 0.79 (15%) ✅ 1.00 (1%)
["scalar", "atan", "(\"19/16 <= abs(x) < 39/16\", \"positive argument\", \"Float64\")"] 0.80 (15%) ✅ 1.00 (1%)
["scalar", "atan", "(\"7/16 <= abs(x) < 11/16\", \"negative argument\", \"Float64\")"] 0.82 (15%) ✅ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 2π/4\", \"negative argument\", \"Float32\", \"sin_kernel\")"] 1.29 (15%) ❌ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 6π/4\", \"negative argument\", \"Float64\", \"sin_kernel\")"] 1.22 (15%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"9f0 <= abs(x) < 88.72283f0\", \"negative argument\", \"Float32\")"] 1.22 (15%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"9f0 <= abs(x) < 88.72283f0\", \"positive argument\", \"Float32\")"] 1.22 (15%) ❌ 1.00 (1%)
["scalar", "expm1", "(\"arg reduction II\", \"negative argument\", \"Float32\")"] 0.80 (15%) ✅ 1.00 (1%)
["scalar", "expm1", "(\"arg reduction I\", \"positive argument\", \"Float32\")"] 1.25 (15%) ❌ 1.00 (1%)
["scalar", "mod2pi", "(\"argument reduction (easy) abs(x) < 8π/4\", \"negative argument\", \"Float64\")"] 1.15 (15%) ❌ 1.00 (1%)
["scalar", "rem_pio2", "(\"argument reduction (easy) abs(x) < 7π/4\", \"positive argument\", \"Float64\")"] 0.50 (15%) ✅ 1.00 (1%)
["scalar", "rem_pio2", "(\"argument reduction (hard) abs(x) < 4π/4\", \"positive argument\", \"Float64\")"] 1.19 (15%) ❌ 1.00 (1%)
["scalar", "sinh", "(\"0 <= abs(x) < 2.0^-28\", \"negative argument\", \"Float64\")"] 0.84 (15%) ✅ 1.00 (1%)
["simd", "(\"conditional_loop!\", \"Int64\", 4095)"] 1.31 (20%) ❌ 1.00 (1%)
["string", "join"] 0.40 (40%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (4,))"] 1.21 (15%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Complex{Float64}, false)"] 0.69 (15%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum\", Int8, true)"] 0.65 (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-beta.38
Commit e9a5fbb (2018-06-26 18:23 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   18765068 s        259 s    2807919 s  764190420 s          5 s
       #2  3501 MHz   93439274 s          0 s    1477471 s  692463889 s          6 s
       #3  3501 MHz   13687786 s       2389 s    1576690 s  772222106 s         12 s
       #4  3501 MHz   13203336 s          4 s    1213725 s  773442056 s          4 s
       
  Memory: 31.383651733398438 GB (2637.33203125 MB free)
  Uptime: 7.882041e6 sec
  Load Avg:  1.0029296875  1.0146484375  1.04541015625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.0 (ORCJIT, haswell)

Comparison Build

Julia Version 0.7.0-beta.33
Commit feb9260 (2018-06-26 17:17 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   18899606 s        259 s    2819227 s  765025275 s          5 s
       #2  3501 MHz   94323441 s          0 s    1488555 s  692552710 s          6 s
       #3  3501 MHz   13804702 s       2389 s    1585370 s  773080252 s         12 s
       #4  3501 MHz   13333690 s          4 s    1222499 s  774287103 s          4 s
       
  Memory: 31.383651733398438 GB (3294.35546875 MB free)
  Uptime: 7.891888e6 sec
  Load Avg:  1.0029296875  1.0146484375  1.04541015625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.0 (ORCJIT, haswell)