Commit(s): JuliaLang/julia@6a23e234e6cc5b4361b5f88614a9ed423dc2c12a
Triggered By: link
Tag Predicate: ALL
Daily Job: 2017-11-12 vs 2017-11-11
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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", "index", "(\"sumvector_view\", \"SubArray{Float32,2,BaseBenchmarks.ArrayBenchmarks.ArrayLS{Float32,3},Tuple{Int64,Base.Slice{Base.OneTo{Int64}},Base.Slice{Base.OneTo{Int64}}},false}\")"] |
1.59 (50%) ❌ | 1.00 (1%) |
["broadcast", "typeargs", "(\"tuple\", 3)"] |
0.56 (15%) ✅ | 1.00 (1%) |
["random", "collections", "(\"rand\", \"ImplicitRNG\", \"small Set\")"] |
1.38 (25%) ❌ | 1.00 (1%) |
["random", "sequences", "(\"randcycle\", \"MersenneTwister\", \"5\")"] |
1.54 (25%) ❌ | 1.00 (1%) |
["random", "types", "(\"rand!\", \"MersenneTwister\", \"Complex{Float64}\")"] |
0.49 (25%) ✅ | 1.00 (1%) |
["random", "types", "(\"rand\", \"ImplicitRNG\", \"Float64\")"] |
0.72 (25%) ✅ | 1.00 (1%) |
["random", "types", "(\"rand\", \"ImplicitRNG\", \"Int64\")"] |
0.75 (25%) ✅ | 1.00 (1%) |
["random", "types", "(\"rand\", \"MersenneTwister\", \"Float64\")"] |
0.68 (25%) ✅ | 1.00 (1%) |
["random", "types", "(\"randn\", \"MersenneTwister\", \"Float64\")"] |
0.75 (25%) ✅ | 1.00 (1%) |
["scalar", "acos", "(\"0.5 <= abs(x) < 1\", \"positive argument\", \"Float64\")"] |
0.79 (15%) ✅ | 1.00 (1%) |
["scalar", "atan2", "(\"x one\", \"Float32\")"] |
1.43 (15%) ❌ | 1.00 (1%) |
["scalar", "atan2", "(\"x one\", \"Float64\")"] |
0.59 (15%) ✅ | 1.00 (1%) |
["scalar", "cos", "(\"argument reduction (hard) abs(x) < 2π/4\", \"positive argument\", \"Float32\", \"sin_kernel\")"] |
1.30 (15%) ❌ | 1.00 (1%) |
["scalar", "intfuncs", "(\"nextpow2\", \"Int64\", \"+\")"] |
0.71 (25%) ✅ | 1.00 (1%) |
["scalar", "intfuncs", "(\"prevpow2\", \"UInt64\", \"+\")"] |
0.64 (25%) ✅ | 1.00 (1%) |
["scalar", "intfuncs", "(\"prevpow2\", \"UInt64\", \"-\")"] |
0.67 (25%) ✅ | 1.00 (1%) |
["scalar", "rem_pio2", "(\"argument reduction (hard) abs(x) < 8π/4\", \"positive argument\", \"Float64\")"] |
1.96 (15%) ❌ | 1.00 (1%) |
["scalar", "sin", "(\"argument reduction (easy) abs(x) < 2π/4\", \"negative argument\", \"Float64\", \"cos_kernel\")"] |
1.21 (15%) ❌ | 1.00 (1%) |
["scalar", "sin", "(\"argument reduction (easy) abs(x) < 3π/4\", \"negative argument\", \"Float64\", \"cos_kernel\")"] |
1.17 (15%) ❌ | 1.00 (1%) |
["scalar", "sin", "(\"argument reduction (easy) abs(x) < 6π/4\", \"negative argument\", \"Float32\", \"cos_kernel\")"] |
0.74 (15%) ✅ | 1.00 (1%) |
["scalar", "sin", "(\"argument reduction (hard) abs(x) < 2π/4\", \"negative argument\", \"Float64\", \"cos_kernel\")"] |
1.30 (15%) ❌ | 1.00 (1%) |
["scalar", "sin", "(\"argument reduction (hard) abs(x) < 4π/4\", \"negative argument\", \"Float64\", \"sin_kernel\")"] |
1.25 (15%) ❌ | 1.00 (1%) |
["scalar", "sin", "(\"argument reduction (hard) abs(x) < 4π/4\", \"positive argument\", \"Float64\", \"sin_kernel\")"] |
1.19 (15%) ❌ | 1.00 (1%) |
["scalar", "sincos", "(\"argument reduction (easy) abs(x) < 6π/4\", \"negative argument\", \"Float32\")"] |
0.78 (15%) ✅ | 1.00 (1%) |
["scalar", "sincos", "(\"argument reduction (easy) abs(x) < 9π/4\", \"negative argument\", \"Float32\")"] |
0.66 (15%) ✅ | 1.00 (1%) |
["scalar", "tan", "(\"large\", \"negative argument\", \"Float32\")"] |
0.84 (15%) ✅ | 1.00 (1%) |
["scalar", "tan", "(\"medium\", \"negative argument\", \"Float32\")"] |
0.83 (15%) ✅ | 1.00 (1%) |
["sparse", "matmul", "(\"A_mul_Bc\", \"dense 500x5, sparse 5x5 -> dense 500x5\")"] |
1.01 (30%) | 1.20 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bc\", \"dense 50x50, sparse 50x50 -> dense 50x50\")"] |
1.03 (30%) | 1.03 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bc\", \"dense 50x50, sparse 5x50 -> dense 50x5\")"] |
0.99 (30%) | 0.90 (1%) ✅ |
["sparse", "matmul", "(\"A_mul_Bc\", \"dense 5x5, sparse 500x5 -> dense 5x500\")"] |
1.01 (30%) | 1.01 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bc\", \"dense 5x50, sparse 500x50 -> dense 5x500\")"] |
1.01 (30%) | 0.81 (1%) ✅ |
["sparse", "matmul", "(\"A_mul_Bc\", \"dense 5x500, sparse 50x500 -> dense 5x50\")"] |
1.00 (30%) | 1.07 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 500x5, sparse 5x5 -> dense 500x5\")"] |
0.98 (30%) | 0.85 (1%) ✅ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 50x5, sparse 50x5 -> dense 50x50\")"] |
1.01 (30%) | 1.02 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 50x50, sparse 50x50 -> dense 50x50\")"] |
1.00 (30%) | 0.55 (1%) ✅ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 5x5, sparse 500x5 -> dense 5x500\")"] |
0.99 (30%) | 0.98 (1%) ✅ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 5x50, sparse 500x50 -> dense 5x500\")"] |
0.99 (30%) | 1.68 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 5x500, sparse 500x500 -> dense 5x500\")"] |
1.01 (30%) | 1.04 (1%) ❌ |
["sparse", "matmul", "(\"A_mul_Bt\", \"dense 5x500, sparse 50x500 -> dense 5x50\")"] |
1.05 (30%) | 1.36 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_B\", \"dense 500x5, sparse 500x50 -> dense 5x50\")"] |
1.02 (30%) | 1.07 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_B\", \"dense 50x5, sparse 50x500 -> dense 5x500\")"] |
1.00 (30%) | 0.81 (1%) ✅ |
["sparse", "matmul", "(\"Ac_mul_B\", \"dense 50x50, sparse 50x5 -> dense 50x5\")"] |
0.98 (30%) | 0.90 (1%) ✅ |
["sparse", "matmul", "(\"Ac_mul_B\", \"dense 50x50, sparse 50x50 -> dense 50x50\")"] |
1.03 (30%) | 1.03 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_B\", \"dense 5x5, sparse 5x500 -> dense 5x500\")"] |
1.00 (30%) | 1.01 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_B\", \"dense 5x500, sparse 5x5 -> dense 500x5\")"] |
1.02 (30%) | 1.20 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_Bc\", \"dense 500x5, sparse 50x500 -> dense 5x50\")"] |
1.00 (30%) | 1.07 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_Bc\", \"dense 50x5, sparse 500x50 -> dense 5x500\")"] |
1.01 (30%) | 0.81 (1%) ✅ |
["sparse", "matmul", "(\"Ac_mul_Bc\", \"dense 50x50, sparse 50x50 -> dense 50x50\")"] |
1.03 (30%) | 1.03 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_Bc\", \"dense 50x50, sparse 5x50 -> dense 50x5\")"] |
1.00 (30%) | 0.90 (1%) ✅ |
["sparse", "matmul", "(\"Ac_mul_Bc\", \"dense 5x5, sparse 500x5 -> dense 5x500\")"] |
1.01 (30%) | 1.01 (1%) ❌ |
["sparse", "matmul", "(\"Ac_mul_Bc\", \"dense 5x500, sparse 5x5 -> dense 500x5\")"] |
1.02 (30%) | 1.20 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 500x5, sparse 500x50 -> dense 5x50\")"] |
1.10 (30%) | 1.36 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 500x5, sparse 500x500 -> dense 5x500\")"] |
1.02 (30%) | 1.04 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 50x5, sparse 50x500 -> dense 5x500\")"] |
0.99 (30%) | 1.68 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 50x50, sparse 50x5 -> dense 50x5\")"] |
1.14 (30%) | 1.94 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 50x50, sparse 50x50 -> dense 50x50\")"] |
1.01 (30%) | 1.11 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 5x5, sparse 5x500 -> dense 5x500\")"] |
1.00 (30%) | 0.98 (1%) ✅ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 5x50, sparse 5x50 -> dense 50x50\")"] |
1.00 (30%) | 1.02 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_B\", \"dense 5x500, sparse 5x5 -> dense 500x5\")"] |
0.97 (30%) | 0.85 (1%) ✅ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 500x5, sparse 500x500 -> dense 5x500\")"] |
1.02 (30%) | 1.04 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 500x5, sparse 50x500 -> dense 5x50\")"] |
1.05 (30%) | 1.36 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 50x5, sparse 500x50 -> dense 5x500\")"] |
0.99 (30%) | 1.68 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 50x50, sparse 50x50 -> dense 50x50\")"] |
1.00 (30%) | 0.55 (1%) ✅ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 5x5, sparse 500x5 -> dense 5x500\")"] |
0.99 (30%) | 0.98 (1%) ✅ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 5x50, sparse 50x5 -> dense 50x50\")"] |
1.01 (30%) | 1.02 (1%) ❌ |
["sparse", "matmul", "(\"At_mul_Bt\", \"dense 5x500, sparse 5x5 -> dense 500x5\")"] |
0.97 (30%) | 0.85 (1%) ✅ |
Here's a list of all the benchmark groups executed by this job:
["array", "bool"]["array", "cat"]["array", "comprehension"]["array", "convert"]["array", "growth"]["array", "index"]["array", "reductions"]["array", "reverse"]["array", "setindex!"]["array", "subarray"]["broadcast", "dotop"]["broadcast", "fusion"]["broadcast", "mix_scalar_tuple"]["broadcast", "sparse"]["broadcast", "typeargs"]["dates", "accessor"]["dates", "arithmetic"]["dates", "construction"]["dates", "conversion"]["dates", "parse"]["dates", "query"]["dates", "string"]["io", "read"]["io", "serialization"]["linalg", "arithmetic"]["linalg", "blas"]["linalg", "factorization"]["micro"]["misc", "afoldl"]["misc", "bitshift"]["misc", "julia"]["misc", "parse"]["misc", "repeat"]["misc", "splatting"]["nullable", "basic"]["nullable", "nullablearray"]["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", "arithmetic"]["scalar", "asin"]["scalar", "atan"]["scalar", "atan2"]["scalar", "cos"]["scalar", "fastmath"]["scalar", "floatexp"]["scalar", "intfuncs"]["scalar", "iteration"]["scalar", "mod2pi"]["scalar", "predicate"]["scalar", "rem_pio2"]["scalar", "sin"]["scalar", "sincos"]["scalar", "tan"]["shootout"]["simd"]["sort", "insertionsort"]["sort", "issorted"]["sort", "mergesort"]["sort", "quicksort"]["sparse", "arithmetic"]["sparse", "constructors"]["sparse", "index"]["sparse", "matmul"]["sparse", "transpose"]["string"]["string", "readuntil"]["string", "search"]["string", "searchindex"]["tuple", "index"]["tuple", "linear algebra"]["tuple", "reduction"]
Julia Version 0.7.0-DEV.2492
Commit 6a23e23 (2017-11-11 22:42 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 100654492 s 0 s 17991228 s 4479427301 s 97 s
#2 3501 MHz 439225401 s 0 s 11635787 s 4157970914 s 21 s
#3 3501 MHz 86939895 s 0 s 9963870 s 4512373939 s 81 s
#4 3501 MHz 83133358 s 0 s 10124641 s 4516031973 s 20 s
Memory: 31.383651733398438 GB (13181.0625 MB free)
Uptime: 4.6115059e7 sec
Load Avg: 1.0029296875 1.0146484375 1.04541015625
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
LAPACK: libopenblas64_
LIBM: libopenlibm
LLVM: libLLVM-3.9.1 (ORCJIT, haswell)