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Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@6a4793ae77490c7704967acb996902661279396e

Triggered By: link

Tag Predicate: ALL

Daily Job: 2020-07-18 vs 2020-07-17

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", "any/all", "(\"any\", \"BitArray\")"] 1.15 (5%) ❌ 1.00 (1%)
["array", "bool", "boolarray_bool_load!"] 0.93 (5%) ✅ 1.00 (1%)
["array", "convert", "(\"Complex{Float64}\", \"Int\")"] 1.05 (5%) ❌ 1.00 (1%)
["array", "index", "4d"] 0.95 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"sumabs\", \"Float64\")"] 0.82 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"sumabs\", \"Int64\")"] 1.05 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", "(\"array\", 10)"] 0.93 (5%) ✅ 1.00 (1%)
["broadcast", "typeargs", "(\"array\", 3)"] 0.92 (5%) ✅ 1.00 (1%)
["collection", "queries & updates", "(\"Dict\", \"Any\", \"push!\", \"new\")"] 1.80 (25%) ❌ 1.00 (1%)
["collection", "queries & updates", "(\"Dict\", \"Int\", \"in\", \"true\")"] 1.67 (25%) ❌ 1.00 (1%)
["collection", "set operations", "(\"Set\", \"Int\", \"intersect\", \"Vector\")"] 1.32 (25%) ❌ 1.00 (1%)
["dates", "parse", "(\"DateTime\", \"ISODateTimeFormat\")"] 1.05 (5%) ❌ 1.00 (1%)
["find", "findall", "(\"BitVector\", \"50-50\")"] 1.07 (5%) ❌ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Vector{Bool}\")"] 0.95 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Vector{UInt64}\")"] 0.87 (5%) ✅ 1.00 (1%)
["io", "array_limit", "(\"display\", \"Matrix{Float64}(10000, 10000)\")"] 1.01 (5%) 1.04 (1%) ❌
["io", "serialization", "(\"serialize\", \"Matrix{Float64}\")"] 1.05 (5%) ❌ 1.00 (1%)
["misc", "20517"] 0.90 (5%) ✅ 1.00 (1%)
["misc", "allocation elision view", "conditional"] 0.78 (5%) ✅ 1.00 (1%)
["misc", "allocation elision view", "no conditional"] 0.88 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"Int\", \"Int\")"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1, 1:1)"] 1.06 (5%) ❌ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000)"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000)"] 0.90 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1000, 1:1000, 1:1000, 1:1000)"] 0.95 (5%) ✅ 1.00 (1%)
["misc", "repeat", "(200, 1, 24)"] 0.91 (5%) ✅ 1.00 (1%)
["misc", "repeat", "(200, 24, 1)"] 0.90 (5%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"large Dict\")"] 1.33 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"MersenneTwister\", \"'a':'z'\")"] 1.29 (25%) ❌ 1.00 (1%)
["random", "collections", "(\"rand\", \"RandomDevice\", \"large Set\")"] 0.59 (25%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"RandomDevice\", \"small Set\")"] 0.67 (25%) ✅ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:2^10000)\")"] 0.73 (25%) ✅ 1.00 (1%)
["scalar", "acos", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "acos", "(\"small\", \"positive argument\", \"Float64\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "acosh", "(\"very large\", \"positive argument\", \"Float32\")"] 0.87 (5%) ✅ 1.00 (1%)
["scalar", "arithmetic", "(\"add\", \"Complex{BigInt}\", \"BigInt\")"] 1.76 (50%) ❌ 1.00 (1%)
["scalar", "arithmetic", "(\"rem type\", \"UInt64\", \"BigInt\")"] 0.56 (40%) ✅ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"negative argument\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) small\", \"y positive\", \"x positive\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) small\", \"y positive\", \"x positive\", \"Float64\")"] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"x one\", \"Float32\")"] 1.47 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"y finite\", \"y negative\", \"x infinite\", \"x negative\", \"Float64\")"] 0.76 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float64\")"] 1.22 (5%) ❌ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (easy) abs(x) < 2π/4\", \"negative argument\", \"Float32\", \"sin_kernel\")"] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (easy) abs(x) < 5π/4\", \"positive argument\", \"Float32\", \"cos_kernel\")"] 0.65 (5%) ✅ 1.00 (1%)
["scalar", "cos", "(\"no reduction\", \"positive argument\", \"Float32\", \"cos_kernel\")"] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "expm1", "(\"huge\", \"positive argument\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "fastmath", "(\"sub\", \"BigInt\")"] 0.55 (40%) ✅ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (easy) abs(x) < 2.0^20π/4\", \"positive argument\", \"Float64\")"] 1.25 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"argument reduction (easy) abs(x) < 3π/4\", \"negative argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"no reduction\", \"negative argument\", \"Float32\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"no reduction\", \"negative argument\", \"Float64\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"no reduction\", \"positive argument\", \"Float32\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sincos", "(\"no reduction\", \"positive argument\", \"Float64\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "sinh", "(\"zero\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"large\", \"negative argument\", \"Float64\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "tanh", "(\"1.0 <= abs(x) < 22.0\", \"negative argument\", \"Float64\")"] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "tanh", "(\"zero\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["sparse", "constructors", "(\"Bidiagonal\", 100)"] 0.93 (5%) ✅ 1.00 (1%)
["sparse", "constructors", "(\"IV\", 1000)"] 1.08 (5%) ❌ 1.00 (1%)
["sparse", "constructors", "(\"SymTridiagonal\", 1000)"] 0.94 (5%) ✅ 1.00 (1%)
["string", "findfirst", "String"] 0.93 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (8,))"] 1.24 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (8,))"] 0.91 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (16,))"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"broadcast\", *, BigInt, (false, true))"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"broadcast\", abs, Bool, true)"] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", "(\"broadcast\", abs, Float64, true)"] 0.76 (5%) ✅ 1.00 (1%)
["union", "array", "(\"broadcast\", identity, ComplexF64, false)"] 0.63 (5%) ✅ 1.00 (1%)
["union", "array", "(\"broadcast\", identity, ComplexF64, true)"] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", *, ComplexF64, (true, true))"] 1.16 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", *, Float64, (false, false))"] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", *, Int64, (true, true))"] 1.24 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", abs, Int8, true)"] 1.15 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", identity, ComplexF64, false)"] 0.61 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_binaryop\", *, ComplexF64, (false, false))"] 1.16 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Float32\")"] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Int64\")"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Int8\")"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", ComplexF64, true)"] 1.31 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", BigFloat, false)"] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", BigFloat, true)"] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Bool, true)"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Float32, true)"] 1.49 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Float64, true)"] 0.71 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Int8, false)"] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Int8, true)"] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", BigFloat, false)"] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", BigFloat, true)"] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float32, true)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum4\", Int8, true)"] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", BigFloat, false)"] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", BigFloat, true)"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Bool, true)"] 1.44 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Float32, true)"] 1.42 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Int8, false)"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum\", Int8, true)"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, BigFloat, false)"] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, BigFloat}, true)"] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Missing, Float64}, true)"] 0.75 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Union{Nothing, BigFloat}, false)"] 1.06 (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 1.6.0-DEV.487
Commit 6a4793a (2020-07-17 20:23 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  150550274 s       5056 s   16955412 s  7105116996 s         38 s
       #2  3501 MHz  1139698970 s        217 s   22893331 s  6120617829 s         28 s
       #3  3501 MHz  135824440 s       3322 s   10094078 s  7136638693 s         39 s
       #4  3501 MHz  127264358 s         43 s   14496106 s  7139174721 s         28 s
       
  Memory: 31.383651733398438 GB (18832.64453125 MB free)
  Uptime: 7.2889407e7 sec
  Load Avg:  1.0029296875  1.0146484375  1.04541015625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-9.0.1 (ORCJIT, haswell)