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Benchmark Report

Job Properties

Commits: JuliaLang/julia@6b81d40a771fca855d0c0e00104314899e7c6c5f vs JuliaLang/julia@572fa5055ecb709edd3d227a10b46549f82b72b2

Comparison Diff: link

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", "cat", ("catnd", 5)] 0.94 (5%) ✅ 1.00 (1%)
["array", "equality", ("==", "BitArray")] 1.06 (5%) ❌ 1.00 (1%)
["array", "equality", ("==", "UnitRange{Int64}")] 0.84 (5%) ✅ 1.00 (1%)
["array", "equality", ("isequal", "UnitRange{Int64}")] 1.10 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Float32}")] 1.08 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Float64}")] 1.10 (5%) ❌ 1.00 (1%)
["array", "equality", ("isequal", "Vector{Int64} isequal Vector{Int64}")] 0.94 (5%) ✅ 1.00 (1%)
["array", "reductions", ("sumabs2", "Float64")] 1.09 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 1)] 1.08 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 2)] 0.93 (5%) ✅ 1.00 (1%)
["array", "setindex!", ("setindex!", 3)] 1.08 (5%) ❌ 1.00 (1%)
["array", "setindex!", ("setindex!", 4)] 0.93 (5%) ✅ 1.00 (1%)
["array", "setindex!", ("setindex!", 5)] 0.93 (5%) ✅ 1.00 (1%)
["broadcast", "dotop", ("Float64", "(1000000,)", 1)] 0.95 (5%) ✅ 1.00 (1%)
["broadcast", "dotop", ("Float64", "(1000000,)", 2)] 0.95 (5%) ✅ 1.00 (1%)
["broadcast", "mix_scalar_tuple", (10, "scal_tup")] 1.09 (5%) ❌ 1.00 (1%)
["collection", "set operations", ("BitSet", "Int", "⊆", "Set")] 1.28 (25%) ❌ 1.00 (1%)
["dates", "parse", ("DateTime", "DateFormat")] 1.07 (5%) ❌ 1.00 (1%)
["inference", "abstract interpretation", "many_opaque_closures"] 1.03 (5%) 1.01 (1%) ❌
["inference", "optimization", "broadcasting"] 0.87 (5%) ✅ 1.00 (1%)
["inference", "optimization", "many_local_vars"] 0.91 (5%) ✅ 1.00 (1%)
["io", "read", "read"] 0.87 (5%) ✅ 1.00 (1%)
["io", "serialization", ("deserialize", "Matrix{Float64}")] 1.10 (5%) ❌ 1.00 (1%)
["linalg", "small exp #29116"] 1.08 (5%) ❌ 1.00 (1%)
["misc", "23042", "ComplexF32"] 1.07 (5%) ❌ 1.00 (1%)
["misc", "23042", "Float64"] 1.08 (5%) ❌ 1.00 (1%)
["misc", "afoldl", "Complex{Float64}"] 0.73 (5%) ✅ 1.00 (1%)
["misc", "allocation elision view", "conditional"] 0.91 (5%) ✅ 1.00 (1%)
["misc", "allocation elision view", "no conditional"] 1.10 (5%) ❌ 1.00 (1%)
["misc", "bitshift", ("UInt32", "UInt32")] 1.20 (5%) ❌ 1.00 (1%)
["misc", "foldl", "foldl(+, filter(...))"] 0.91 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1)"] 0.91 (5%) ✅ 1.00 (1%)
["misc", "iterators", "zip(1:1, 1:1, 1:1, 1:1)"] 1.20 (5%) ❌ 1.00 (1%)
["misc", "julia", ("parse", "array")] 1.08 (5%) ❌ 1.00 (1%)
["misc", "julia", ("parse", "function")] 0.90 (5%) ✅ 1.00 (1%)
["misc", "julia", ("parse", "nested")] 0.91 (5%) ✅ 1.00 (1%)
["problem", "simplex", "simplex"] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "acos", ("0.5 <= abs(x) < 1", "negative argument", "Float64")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "acos", ("one", "negative argument", "Float32")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "acos", ("one", "negative argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "acos", ("one", "positive argument", "Float32")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "acos", ("one", "positive argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "acos", ("small", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "acos", ("small", "positive argument", "Float32")] 1.16 (5%) ❌ 1.00 (1%)
["scalar", "acosh", ("one", "Float32")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "acosh", ("one", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "arithmetic", ("div", "UInt64", "UInt64")] 0.71 (25%) ✅ 1.00 (1%)
["scalar", "asin", ("one", "negative argument", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "asin", ("one", "positive argument", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "asin", ("small", "negative argument", "Float32")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "asin", ("small", "positive argument", "Float32")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "asin", ("zero", "Float32")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "asinh", ("very large", "negative argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "asinh", ("very large", "positive argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "asinh", ("very small", "negative argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "asinh", ("very small", "positive argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "asinh", ("zero", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("very large", "negative argument", "Float32")] 1.12 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("very large", "positive argument", "Float32")] 1.12 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("very small", "negative argument", "Float32")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("very small", "positive argument", "Float32")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "atan", ("zero", "Float32")] 0.85 (5%) ✅ 1.00 (1%)
["scalar", "atan2", ("abs(y/x) high", "y infinite", "y negative", "x finite", "x negative", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("abs(y/x) high", "y negative", "x negative", "Float32")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("abs(y/x) high", "y positive", "x negative", "Float32")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("abs(y/x) small", "y positive", "x negative", "Float32")] 1.10 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("x one", "Float32")] 1.43 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y finite", "y positive", "x infinite", "x positive", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y infinite", "y negative", "x finite", "x negative", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y infinite", "y negative", "x finite", "x positive", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y infinite", "y negative", "x infinite", "x negative", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y infinite", "y positive", "x finite", "x negative", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y infinite", "y positive", "x finite", "x positive", "Float32")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y infinite", "y positive", "x infinite", "x negative", "Float32")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y zero", "y negative", "x positive", "Float32")] 1.10 (5%) ❌ 1.00 (1%)
["scalar", "atan2", ("y zero", "y negative", "x positive", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "atan2", ("y zero", "y positive", "x positive", "Float32")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "atanh", ("zero", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "cbrt", ("large", "negative argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "cbrt", ("large", "positive argument", "Float32")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "cbrt", ("zero", "Float32")] 0.88 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 2π/4", "negative argument", "Float32", "sin_kernel")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 2π/4", "negative argument", "Float64", "sin_kernel")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 2π/4", "positive argument", "Float32", "sin_kernel")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 2π/4", "positive argument", "Float64", "sin_kernel")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 3π/4", "negative argument", "Float32", "sin_kernel")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 3π/4", "negative argument", "Float64", "sin_kernel")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 3π/4", "positive argument", "Float32", "sin_kernel")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 3π/4", "positive argument", "Float64", "sin_kernel")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 4π/4", "positive argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 4π/4", "positive argument", "Float64", "cos_kernel")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 5π/4", "positive argument", "Float32", "cos_kernel")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 5π/4", "positive argument", "Float64", "cos_kernel")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 6π/4", "positive argument", "Float32", "sin_kernel")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 6π/4", "positive argument", "Float64", "sin_kernel")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 7π/4", "positive argument", "Float32", "cos_kernel")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (easy) abs(x) < 7π/4", "positive argument", "Float64", "cos_kernel")] 1.08 (5%) ❌ 1.00 (1%)
["scalar", "cos", ("argument reduction (hard) abs(x) < 4π/4", "negative argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "cos", ("argument reduction (hard) abs(x) < 4π/4", "positive argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "cosh", ("0 <= abs(x) < 0.00024414062f0", "negative argument", "Float32")] 1.13 (5%) ❌ 1.00 (1%)
["scalar", "cosh", ("0 <= abs(x) < 0.00024414062f0", "positive argument", "Float32")] 0.88 (5%) ✅ 1.00 (1%)
["scalar", "cosh", ("very large", "negative argument", "Float64")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "cosh", ("very large", "positive argument", "Float64")] 1.09 (5%) ❌ 1.00 (1%)
["scalar", "cosh", ("very small", "negative argument", "Float32")] 1.14 (5%) ❌ 1.00 (1%)
["scalar", "cosh", ("very small", "positive argument", "Float32")] 0.89 (5%) ✅ 1.00 (1%)
["scalar", "cosh", ("zero", "Float32")] 1.14 (5%) ❌ 1.00 (1%)
["scalar", "exp2", ("2pow35", "negative argument", "Float32")] 1.20 (5%) ❌ 1.00 (1%)
["scalar", "exp2", ("2pow35", "positive argument", "Float32")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "expm1", ("huge", "positive argument", "Float3")] 1.17 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("large", "negative argument", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "expm1", ("large", "positive argument", "Float32")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("large", "positive argument", "Float64")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "expm1", ("medium", "negative argument", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "expm1", ("medium", "positive argument", "Float32")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "fastmath", "13786"] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "mod2pi", ("no reduction", "negative argument", "Float64")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 2.0^20π/4", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 2π/4", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 3π/4", "positive argument", "Float64")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 4π/4", "positive argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 5π/4", "positive argument", "Float64")] 1.06 (5%) ❌ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 6π/4", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 6π/4", "positive argument", "Float64")] 1.22 (5%) ❌ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 7π/4", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (easy) abs(x) < 7π/4", "positive argument", "Float64")] 0.86 (5%) ✅ 1.00 (1%)
["scalar", "rem_pio2", ("argument reduction (hard) abs(x) < 8π/4", "positive argument", "Float64")] 0.84 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (easy) abs(x) < 2π/4", "negative argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (easy) abs(x) < 3π/4", "negative argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (easy) abs(x) < 6π/4", "positive argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (easy) abs(x) < 7π/4", "positive argument", "Float32", "sin_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (hard) abs(x) < 2π/4", "negative argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (hard) abs(x) < 2π/4", "negative argument", "Float64", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("argument reduction (hard) abs(x) < 6π/4", "positive argument", "Float32", "cos_kernel")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("no reduction", "zero", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sin", ("no reduction", "zero", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 2π/4", "negative argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 2π/4", "negative argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 2π/4", "positive argument", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 2π/4", "positive argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 3π/4", "negative argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 3π/4", "negative argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 3π/4", "positive argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 3π/4", "positive argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 4π/4", "negative argument", "Float32")] 0.85 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 4π/4", "negative argument", "Float64")] 0.85 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 4π/4", "positive argument", "Float32")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 4π/4", "positive argument", "Float64")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 5π/4", "negative argument", "Float32")] 0.85 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 5π/4", "negative argument", "Float64")] 0.85 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 5π/4", "positive argument", "Float32")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 5π/4", "positive argument", "Float64")] 0.83 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 6π/4", "negative argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 6π/4", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 6π/4", "positive argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 6π/4", "positive argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 7π/4", "negative argument", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 7π/4", "negative argument", "Float64")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 7π/4", "positive argument", "Float32")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 7π/4", "positive argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 8π/4", "negative argument", "Float32")] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 8π/4", "negative argument", "Float64")] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 8π/4", "positive argument", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 8π/4", "positive argument", "Float64")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 9π/4", "negative argument", "Float32")] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 9π/4", "negative argument", "Float64")] 0.91 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 9π/4", "positive argument", "Float32")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (easy) abs(x) < 9π/4", "positive argument", "Float64")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "sincos", ("argument reduction (hard) abs(x) < 4π/4", "negative argument", "Float32")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "sincos", ("argument reduction (hard) abs(x) < 4π/4", "positive argument", "Float32")] 1.05 (5%) ❌ 1.00 (1%)
["scalar", "sinh", ("very large", "negative argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "sinh", ("very large", "positive argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "sinh", ("zero", "Float32")] 0.92 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("large", "positive argument", "Float64")] 1.11 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("medium", "negative argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("medium", "negative argument", "Float64")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("small", "negative argument", "Float32")] 1.18 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("small", "negative argument", "Float64")] 0.89 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("small", "positive argument", "Float32")] 1.17 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("small", "positive argument", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("very small", "negative argument", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("very small", "negative argument", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("very small", "positive argument", "Float32")] 1.18 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("very small", "positive argument", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "tan", ("zero", "Float32")] 1.17 (5%) ❌ 1.00 (1%)
["scalar", "tan", ("zero", "Float64")] 0.90 (5%) ✅ 1.00 (1%)
["scalar", "tanh", ("2f0^-12 <= abs(x) < 1f0", "negative argument", "Float32")] 0.95 (5%) ✅ 1.00 (1%)
["scalar", "tanh", ("very large", "negative argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("very large", "negative argument", "Float64")] 0.93 (5%) ✅ 1.00 (1%)
["scalar", "tanh", ("very large", "positive argument", "Float32")] 1.07 (5%) ❌ 1.00 (1%)
["scalar", "tanh", ("very large", "positive argument", "Float64")] 0.94 (5%) ✅ 1.00 (1%)
["simd", ("Cartesian", "conditional_loop!", "Int32", 2, 31)] 1.41 (20%) ❌ 1.00 (1%)
["simd", ("CartesianPartition", "conditional_loop!", "Int32", 2, 31)] 1.22 (20%) ❌ 1.00 (1%)
["sort", "issorted", ("reverse", "ascending")] 0.13 (30%) ✅ 1.00 (1%)
["sort", "issorted", ("reverse", "random")] 0.14 (30%) ✅ 1.00 (1%)
["sparse", "matmul", ("A_mul_B!", "sparse 4000x40, dense 40x40 -> dense 4000x40")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 4000x400, dense 400x40 -> dense 4000x40")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 4000x4000, dense 4000x40 -> dense 4000x40")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 400x40, dense 40x400 -> dense 400x400")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 400x400, dense 400x400 -> dense 400x400")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 400x4000, dense 4000x40 -> dense 400x40")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 40x40, dense 40x4000 -> dense 40x4000")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B!", "sparse 40x400, dense 400x400 -> dense 40x400")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("A_mul_B", "sparse 50x500, dense 500x5 -> dense 50x5")] 1.00 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("A_mul_B", "sparse 5x50, dense 50x50 -> dense 5x50")] 1.00 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 2000x20, dense 20x20 -> dense 2000x20")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 2000x200, dense 20x200 -> dense 2000x20")] 1.01 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 2000x2000, dense 20x2000 -> dense 2000x20")] 1.04 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 200x20, dense 200x20 -> dense 200x200")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 200x200, dense 200x200 -> dense 200x200")] 1.01 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 200x2000, dense 20x2000 -> dense 200x20")] 1.06 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 20x20, dense 2000x20 -> dense 20x2000")] 1.01 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc!", "sparse 20x200, dense 200x200 -> dense 20x200")] 1.01 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bc", "sparse 50x500, dense 5x500 -> dense 50x5")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("A_mul_Bc", "sparse 5x50, dense 50x50 -> dense 5x50")] 1.00 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 4000x40, dense 40x40 -> dense 4000x40")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 4000x400, dense 40x400 -> dense 4000x40")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 4000x4000, dense 40x4000 -> dense 4000x40")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 400x40, dense 400x40 -> dense 400x400")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 400x400, dense 400x400 -> dense 400x400")] 0.97 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 400x4000, dense 40x4000 -> dense 400x40")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 40x40, dense 4000x40 -> dense 40x4000")] 0.95 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt!", "sparse 40x400, dense 400x400 -> dense 40x400")] 1.05 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("A_mul_Bt", "sparse 50x500, dense 5x500 -> dense 50x5")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("A_mul_Bt", "sparse 5x50, dense 50x50 -> dense 5x50")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 2000x200, dense 2000x20 -> dense 200x20")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 2000x2000, dense 2000x20 -> dense 2000x20")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 200x20, dense 200x200 -> dense 20x200")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 200x200, dense 200x200 -> dense 200x200")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 200x2000, dense 200x20 -> dense 2000x20")] 1.01 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 20x20, dense 20x2000 -> dense 20x2000")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 20x200, dense 20x200 -> dense 200x200")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B!", "sparse 20x2000, dense 20x20 -> dense 2000x20")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("Ac_mul_B", "sparse 500x50, dense 500x5 -> dense 50x5")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("Ac_mul_B", "sparse 50x5, dense 50x50 -> dense 5x50")] 1.00 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 2000x200, dense 20x2000 -> dense 200x20")] 0.99 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 2000x2000, dense 20x2000 -> dense 2000x20")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 200x20, dense 200x200 -> dense 20x200")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 200x200, dense 200x200 -> dense 200x200")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 200x2000, dense 20x200 -> dense 2000x20")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 20x20, dense 2000x20 -> dense 20x2000")] 0.99 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 20x200, dense 200x20 -> dense 200x200")] 1.01 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc!", "sparse 20x2000, dense 20x20 -> dense 2000x20")] 1.02 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc", "sparse 500x50, dense 5x500 -> dense 50x5")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("Ac_mul_Bc", "sparse 50x5, dense 50x50 -> dense 5x50")] 1.00 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 4000x400, dense 4000x40 -> dense 400x40")] 1.01 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 4000x4000, dense 4000x40 -> dense 4000x40")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 400x40, dense 400x400 -> dense 40x400")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 400x400, dense 400x400 -> dense 400x400")] 1.01 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 400x4000, dense 400x40 -> dense 4000x40")] 1.01 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 40x40, dense 40x4000 -> dense 40x4000")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 40x400, dense 40x400 -> dense 400x400")] 1.00 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B!", "sparse 40x4000, dense 40x40 -> dense 4000x40")] 1.14 (30%) 0.00 (1%) ✅
["sparse", "matmul", ("At_mul_B", "sparse 500x50, dense 500x5 -> dense 50x5")] 1.01 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("At_mul_B", "sparse 50x5, dense 50x50 -> dense 5x50")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 4000x400, dense 40x4000 -> dense 400x40")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 4000x4000, dense 40x4000 -> dense 4000x40")] 1.05 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 400x40, dense 400x400 -> dense 40x400")] 1.01 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 400x400, dense 400x400 -> dense 400x400")] 0.98 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 400x4000, dense 40x400 -> dense 4000x40")] 0.98 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 40x40, dense 4000x40 -> dense 40x4000")] 1.02 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 40x400, dense 400x40 -> dense 400x400")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt!", "sparse 40x4000, dense 40x40 -> dense 4000x40")] 1.00 (30%) 0.25 (1%) ✅
["sparse", "matmul", ("At_mul_Bt", "sparse 500x50, dense 5x500 -> dense 50x5")] 0.99 (30%) 0.99 (1%) ✅
["sparse", "matmul", ("At_mul_Bt", "sparse 50x5, dense 50x50 -> dense 5x50")] 0.99 (30%) 0.99 (1%) ✅
["tuple", "linear algebra", ("matmat", "(4, 4)", "(4, 4)")] 1.61 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(16, 16)", "(16,)")] 1.31 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(4, 4)", "(4,)")] 1.19 (5%) ❌ 1.00 (1%)
["tuple", "linear algebra", ("matvec", "(8, 8)", "(8,)")] 0.91 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(4,)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("minimum", "(8, 8)")] 0.94 (5%) ✅ 1.00 (1%)
["tuple", "reduction", ("sum", "(2, 2)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(4,)")] 1.07 (5%) ❌ 1.00 (1%)
["tuple", "reduction", ("sum", "(8, 8)")] 0.80 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "*", "BigInt", "(false, false)")] 1.11 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "BigInt", "(false, true)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "BigInt", "(true, true)")] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float32", "(false, false)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "*", "Float32", "(false, true)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Float64", 0)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("broadcast", "identity", "Int8", 1)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("collect", "all", "BigFloat", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "BigInt", "(false, false)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "BigInt", "(false, true)")] 1.08 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "BigInt", "(true, true)")] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "ComplexF64", "(false, true)")] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "*", "Float32", "(false, true)")] 1.12 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float32", "(true, true)")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float64", "(false, false)")] 1.07 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float64", "(false, true)")] 1.15 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Float64", "(true, true)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "*", "Int64", "(false, false)")] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("map", "identity", "BigFloat", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("map", "identity", "Float32", 1)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "BigInt", "(false, false)")] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "BigInt", "(false, true)")] 1.09 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "BigInt", "(true, true)")] 1.10 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Float64", "(false, true)")] 0.90 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_binaryop", "*", "Int8", "(false, true)")] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_simplecopy", "Int64", 1)] 1.17 (5%) ❌ 1.00 (1%)
["union", "array", ("perf_sum2", "Int8", 0)] 0.95 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "ComplexF64", 1)] 0.91 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float32", 1)] 0.94 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Float64", 1)] 0.89 (5%) ✅ 1.00 (1%)
["union", "array", ("perf_sum3", "Int64", 1)] 0.87 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "collect", "Union{Missing, Bool}", 1)] 1.06 (5%) ❌ 1.00 (1%)
["union", "array", ("skipmissing", "keys", "BigInt", 0)] 0.92 (5%) ✅ 1.00 (1%)
["union", "array", ("skipmissing", "sum", "Union{Missing, BigFloat}", 1)] 0.93 (5%) ✅ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["alloc"]
  • ["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"]
  • ["frontend"]
  • ["inference", "abstract interpretation"]
  • ["inference", "allinference"]
  • ["inference", "optimization"]
  • ["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", "foldl"]
  • ["misc", "issue 12165"]
  • ["misc", "iterators"]
  • ["misc", "julia"]
  • ["misc", "parse"]
  • ["misc", "repeat"]
  • ["misc", "splatting"]
  • ["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", "==(::AbstractString, ::AbstractString)"]
  • ["string", "==(::SubString, ::String)"]
  • ["string", "findfirst"]
  • ["string"]
  • ["string", "readuntil"]
  • ["string", "repeat"]
  • ["tuple", "index"]
  • ["tuple", "linear algebra"]
  • ["tuple", "misc"]
  • ["tuple", "reduction"]
  • ["union", "array"]

Version Info

Primary Build

Julia Version 1.11.0-DEV.459
Commit 6b81d40a77 (2023-09-13 14:23 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.3 LTS
  uname: Linux 5.15.0-76-generic #83-Ubuntu SMP Thu Jun 15 19:16:32 UTC 2023 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1   900 MHz     209809 s         79 s      90918 s   59332972 s          0 s
       #2   800 MHz    5673360 s         83 s     168694 s   53801577 s          0 s
       #3   800 MHz     202167 s         77 s      85145 s   59291025 s          0 s
       #4   800 MHz     170646 s         51 s      91714 s   59305693 s          0 s
       #5  2500 MHz     162536 s         61 s      96586 s   59113516 s          0 s
       #6  3500 MHz     176404 s         69 s      89376 s   59343906 s          0 s
       #7   800 MHz     185897 s         33 s     110486 s   59333268 s          0 s
       #8   800 MHz     175430 s         42 s      80376 s   59373321 s          0 s
  Memory: 31.301593780517578 GB (22743.9140625 MB free)
  Uptime: 5.96987125e6 sec
  Load Avg:  1.22  1.08  1.02
  WORD_SIZE: 64
  LLVM: libLLVM-15.0.7 (ORCJIT, haswell)
  Threads: 1 on 8 virtual cores

Comparison Build

Julia Version 1.11.0-DEV.455
Commit 572fa5055e (2023-09-13 10:35 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.3 LTS
  uname: Linux 5.15.0-76-generic #83-Ubuntu SMP Thu Jun 15 19:16:32 UTC 2023 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz: 
              speed         user         nice          sys         idle          irq
       #1   800 MHz     210559 s         79 s      91770 s   59458594 s          0 s
       #2  3500 MHz    5798009 s         83 s     170592 s   53802999 s          0 s
       #3  2600 MHz     202644 s         77 s      85170 s   59418383 s          0 s
       #4  3100 MHz     170693 s         51 s      91726 s   59433453 s          0 s
       #5   800 MHz     162722 s         61 s      96600 s   59241076 s          0 s
       #6   800 MHz     176833 s         69 s      89391 s   59471416 s          0 s
       #7  3700 MHz     186319 s         33 s     110504 s   59460776 s          0 s
       #8  3800 MHz     175480 s         42 s      80393 s   59501182 s          0 s
  Memory: 31.301593780517578 GB (22710.390625 MB free)
  Uptime: 5.98266838e6 sec
  Load Avg:  1.05  1.02  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-15.0.7 (ORCJIT, haswell)
  Threads: 1 on 8 virtual cores