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Benchmark Report

Job Properties

Commit(s): JuliaLang/julia@caefb9b7493b62b5c5574503350e3f3cf9a36312 vs JuliaLang/julia@38612e03bcbdce12bebf9180faefbfad9d1739c3

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", "(\"cumsum!\", \"Float64\", \"dim2\")"] 0.91 (5%) ✅ 1.00 (1%)
["array", "accumulate", "(\"cumsum\", \"Float64\", \"dim1\")"] 0.94 (5%) ✅ 1.00 (1%)
["array", "any/all", "(\"any\", \"BitArray\")"] 0.95 (5%) ✅ 1.00 (1%)
["array", "cat", "(\"catnd\", 5)"] 0.95 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"collect\", \"Array{Float64,1}\")"] 0.65 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 0.76 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"Array{Float64,1}\")"] 0.67 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_collect\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 0.76 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_iteration\", \"Array{Float64,1}\")"] 0.86 (5%) ✅ 1.00 (1%)
["array", "comprehension", "(\"comprehension_iteration\", \"StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}\")"] 0.88 (5%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Int64,1} == UnitRange{Int64}\")"] 0.89 (5%) ✅ 1.00 (1%)
["array", "equality", "(\"==\", \"Array{Int64,1}\")"] 1.07 (5%) ❌ 1.00 (1%)
["array", "equality", "(\"==\", \"BitArray\")"] 0.94 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"append!\", 2048)"] 0.93 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"prerend!\", 2048)"] 0.86 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"push_multiple!\", 8)"] 0.94 (5%) ✅ 1.00 (1%)
["array", "growth", "(\"push_single!\", 256)"] 0.94 (5%) ✅ 1.00 (1%)
["array", "reductions", "(\"BaseBenchmarks.ArrayBenchmarks.perf_mapreduce\", \"Int64\")"] 1.05 (5%) ❌ 1.00 (1%)
["array", "reductions", "(\"sumabs2\", \"Float64\")"] 1.07 (5%) ❌ 1.00 (1%)
["array", "reverse", "rev_load_slow!"] 0.93 (5%) ✅ 1.00 (1%)
["array", "setindex!", "(\"setindex!\", 3)"] 0.95 (5%) ✅ 1.00 (1%)
["array", "setindex!", "(\"setindex!\", 4)"] 0.94 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 1000)"] 0.87 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 250)"] 0.88 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivCopy!\", 500)"] 0.87 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 1000)"] 0.89 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 250)"] 0.91 (5%) ✅ 1.00 (1%)
["array", "subarray", "(\"lucompletepivSub!\", 500)"] 0.88 (5%) ✅ 1.00 (1%)
["broadcast", "dotop", "(\"Float64\", (1000, 1000), 2)"] 0.93 (5%) ✅ 1.00 (1%)
["broadcast", "dotop", "(\"Float64\", (1000000,), 1)"] 0.94 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", "(3, \"scal_tup_x3\")"] 1.20 (5%) ❌ 1.00 (1%)
["broadcast", "sparse", "((1000, 1000), 2)"] 1.06 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", "(\"array\", 10)"] 1.06 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", "(\"array\", 3)"] 1.07 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", "(\"array\", 5)"] 1.09 (5%) ❌ 1.00 (1%)
["broadcast", "typeargs", "(\"tuple\", 10)"] 0.82 (5%) ✅ 1.00 (1%)
["broadcast", "typeargs", "(\"tuple\", 5)"] 0.74 (5%) ✅ 1.00 (1%)
["collection", "deletion", "(\"Vector\", \"Any\", \"filter\")"] 1.45 (25%) ❌ 1.00 (1%)
["collection", "queries & updates", "(\"BitSet\", \"Int\", \"in\", \"true\")"] 0.74 (25%) ✅ 1.00 (1%)
["collection", "set operations", "(\"BitSet\", \"Int\", \"union!\", \"big\")"] 0.75 (25%) ✅ 1.00 (1%)
["dates", "parse", "(\"Date\", \"DateFormat\")"] 0.95 (5%) ✅ 1.00 (1%)
["dates", "string", "DateTime"] 0.95 (5%) ✅ 1.00 (1%)
["find", "findall", "(\"Array{Bool,1}\", \"10-90\")"] 1.08 (5%) ❌ 1.00 (1%)
["find", "findall", "(\"BitArray{1}\", \"10-90\")"] 0.93 (5%) ✅ 1.00 (1%)
["find", "findall", "(\"BitArray{1}\", \"90-10\")"] 0.88 (5%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Float32,1}\")"] 0.85 (5%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{Int8,1}\")"] 0.95 (5%) ✅ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{UInt64,1}\")"] 1.05 (5%) ❌ 1.00 (1%)
["find", "findnext", "(\"ispos\", \"Array{UInt8,1}\")"] 0.93 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{Bool,1}\")"] 0.84 (5%) ✅ 1.00 (1%)
["find", "findprev", "(\"ispos\", \"Array{UInt64,1}\")"] 1.06 (5%) ❌ 1.00 (1%)
["misc", "23042", "Float64"] 0.84 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"Int\", \"Int\")"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"Int\", \"UInt\")"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"UInt32\", \"UInt32\")"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "bitshift", "(\"UInt\", \"UInt\")"] 0.93 (5%) ✅ 1.00 (1%)
["misc", "splatting", "(3, 3, 3)"] 0.94 (5%) ✅ 1.00 (1%)
["parallel", "remotecall", "(\"identity\", 1024)"] 1.10 (5%) ❌ 1.00 (1%)
["parallel", "remotecall", "(\"identity\", 2)"] 1.12 (5%) ❌ 1.00 (1%)
["parallel", "remotecall", "(\"identity\", 4096)"] 1.10 (5%) ❌ 1.00 (1%)
["parallel", "remotecall", "(\"identity\", 512)"] 1.12 (5%) ❌ 1.00 (1%)
["parallel", "remotecall", "(\"identity\", 64)"] 1.12 (5%) ❌ 1.00 (1%)
["problem", "fem", "sparse_fem"] 0.91 (5%) ✅ 1.00 (1%)
["problem", "go", "go_game"] 0.91 (5%) ✅ 1.00 (1%)
["problem", "grigoriadis khachiyan", "grigoriadis_khachiyan"] 0.86 (5%) ✅ 1.00 (1%)
["problem", "imdb", "centrality"] 0.92 (5%) ✅ 1.00 (1%)
["problem", "laplacian", "laplace_iter_sub"] 0.88 (5%) ✅ 1.00 (1%)
["problem", "laplacian", "laplace_iter_vec"] 0.85 (5%) ✅ 1.00 (1%)
["problem", "laplacian", "laplace_sparse_matvec"] 0.88 (5%) ✅ 1.00 (1%)
["problem", "raytrace", "raytrace"] 0.93 (5%) ✅ 1.00 (1%)
["problem", "stockcorr", "stockcorr"] 0.92 (5%) ✅ 1.00 (1%)
["problem", "ziggurat", "ziggurat"] 0.87 (5%) ✅ 1.00 (1%)
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"large Set\")"] 0.69 (25%) ✅ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:18446744073709551616)\")"] 0.73 (25%) ✅ 1.00 (1%)
["random", "ranges", "(\"rand\", \"MersenneTwister\", \"BigInt\", \"RangeGenerator(1:2^10000)\")"] 0.70 (25%) ✅ 1.00 (1%)
["scalar", "acos", "(\"abs(x) < 0.5\", \"positive argument\", \"Float64\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "acos", "(\"small\", \"negative argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"positive argument\", \"Float32\")"] 0.86 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"0.5 <= abs(x) < 0.975\", \"positive argument\", \"Float64\")"] 0.75 (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\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"abs(x) < 0.5\", \"negative argument\", \"Float32\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"abs(x) < 0.5\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"abs(x) < 0.5\", \"positive argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"small\", \"positive argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"zero\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asin", "(\"zero\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asinh", "(\"0 <= abs(x) < 2^-28\", \"positive argument\", \"Float32\")"] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "atan", "(\"7/16 <= abs(x) < 11/16\", \"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\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) safe (small)\", \"y negative\", \"x negative\", \"Float32\")"] 0.82 (5%) ✅ 1.00 (1%)
["scalar", "atan2", "(\"abs(y/x) small\", \"y positive\", \"x positive\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float32\")"] 0.80 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"negative argument\", \"Float64\")"] 0.82 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"positive argument\", \"Float32\")"] 0.80 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"0.5 <= abs(x) < 1\", \"positive argument\", \"Float64\")"] 0.78 (5%) ✅ 1.00 (1%)
["scalar", "atanh", "(\"very small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "cos", "(\"argument reduction (easy) abs(x) < 8π/4\", \"negative argument\", \"Float64\", \"cos_kernel\")"] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "cos", "(\"no reduction\", \"positive argument\", \"Float64\", \"cos_kernel\")"] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "cosh", "(\"0 <= abs(x) < 0.00024414062f0\", \"negative argument\", \"Float32\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "cosh", "(\"0 <= abs(x) < 0.00024414062f0\", \"positive argument\", \"Float32\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "cosh", "(\"very large\", \"positive argument\", \"Float32\")"] 0.86 (5%) ✅ 1.00 (1%)
["scalar", "cosh", "(\"very small\", \"negative argument\", \"Float32\")"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "cosh", "(\"very small\", \"positive argument\", \"Float32\")"] 0.86 (5%) ✅ 1.00 (1%)
["scalar", "cosh", "(\"zero\", \"Float32\")"] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"2pow1023\", \"negative argument\", Float64)"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"2pow127\", \"negative argument\", Float32)"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "exp2", "(\"very small\", \"positive argument\", \"Float32\")"] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "expm1", "(\"large\", \"negative argument\", \"Float32\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "expm1", "(\"very small\", \"positive argument\", \"Float64\")"] 1.20 (5%) ❌ 1.00 (1%)
["scalar", "mod2pi", "(\"argument reduction (hard) abs(x) < 8π/4\", \"positive argument\", \"Float64\")"] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "tan", "(\"small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"small\", \"positive argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"negative argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"positive argument\", \"Float32\")"] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "tan", "(\"very small\", \"positive argument\", \"Float64\")"] 0.94 (5%) ✅ 1.00 (1%)
["shootout", "binary_trees"] 1.08 (5%) ❌ 1.00 (1%)
["shootout", "k_nucleotide"] 0.95 (5%) ✅ 1.00 (1%)
["shootout", "pidigits"] 0.92 (5%) ✅ 1.00 (1%)
["sparse", "constructors", "(\"Diagonal\", 100)"] 0.92 (5%) ✅ 1.00 (1%)
["sparse", "transpose", "(\"transpose\", (600, 400))"] 0.68 (30%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (16,))"] 0.93 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"minimum\", (4,))"] 1.06 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sum\", (4, 4))"] 1.55 (5%) ❌ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (2, 2))"] 0.82 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (4,))"] 0.88 (5%) ✅ 1.00 (1%)
["tuple", "reduction", "(\"sumabs\", (8,))"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", *, Bool, (false, true))"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", *, Complex{Float64}, (true, true))"] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", abs, Bool, false)"] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", "(\"map\", abs, Float64, true)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", abs, Int8, false)"] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", identity, BigFloat, false)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", identity, BigInt, true)"] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", identity, Complex{Float64}, true)"] 0.86 (5%) ✅ 1.00 (1%)
["union", "array", "(\"map\", identity, Int8, false)"] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_binaryop\", *, Int64, (true, true))"] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Bool\")"] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_countequals\", \"Float32\")"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", BigFloat, false)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", BigInt, true)"] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_simplecopy\", Int8, true)"] 0.84 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum2\", Bool, true)"] 0.93 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Complex{Float64}, true)"] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum3\", Float32, true)"] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", "(\"perf_sum4\", Complex{Float64}, true)"] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum4\", Int8, false)"] 0.88 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum\", Float64, true)"] 0.82 (5%) ✅ 1.00 (1%)
["union", "array", "(\"perf_sum\", Int8, true)"] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", collect, Int64, false)"] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", collect, Int64, true)"] 1.05 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, BigFloat, true)"] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Bool, true)"] 1.21 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Complex{Float64}, true)"] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Float32, true)"] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", "(\"skipmissing\", sum, Float64, true)"] 0.87 (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", "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"]
  • ["io"]
  • ["linalg", "arithmetic"]
  • ["linalg", "blas"]
  • ["linalg", "factorization"]
  • ["micro"]
  • ["misc"]
  • ["misc", "23042"]
  • ["misc", "afoldl"]
  • ["misc", "bitshift"]
  • ["misc", "issue 12165"]
  • ["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", "misc"]
  • ["tuple", "reduction"]
  • ["union", "array"]

Version Info

Primary Build

Julia Version 1.1.0-DEV.434
Commit caefb9b (2018-10-08 20:56 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   34389875 s       2410 s    5397699 s  1648140259 s          9 s
       #2  3501 MHz  171231458 s          9 s    3102708 s  1517297553 s         15 s
       #3  3501 MHz   25650980 s       3131 s    3038979 s  1662706633 s         22 s
       #4  3501 MHz   24627006 s         11 s    2394138 s  1665241260 s         16 s
       
  Memory: 31.383651733398438 GB (5427.82421875 MB free)
  Uptime: 1.6930564e7 sec
  Load Avg:  0.9228515625  1.0009765625  1.0400390625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, haswell)

Comparison Build

Julia Version 1.1.0-DEV.431
Commit 38612e0 (2018-10-08 19:30 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   34523286 s       2410 s    5409157 s  1649279410 s          9 s
       #2  3501 MHz  172373734 s          9 s    3118683 s  1517427683 s         15 s
       #3  3501 MHz   25778144 s       3131 s    3046313 s  1663859993 s         22 s
       #4  3501 MHz   24740296 s         11 s    2401198 s  1666409374 s         16 s
       
  Memory: 31.383651733398438 GB (4597.98046875 MB free)
  Uptime: 1.6943456e7 sec
  Load Avg:  0.97412109375  0.998046875  1.0400390625
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, haswell)