Commits: JuliaLang/julia@1493b89a5808e61a378560bfb00d34c6561c0fc5 vs JuliaLang/julia@18bdbbffd7434cf333e893f84a2ceff5459d21a9
Comparison Diff: link
Triggered By: link
Tag Predicate: "inference"
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 |
---|---|---|
["inference", "abstract interpretation", "abstract_call_gf_by_type"] |
1.02 (5%) | 0.96 (1%) ✅ |
["inference", "abstract interpretation", "construct_ssa!"] |
1.00 (5%) | 0.95 (1%) ✅ |
["inference", "abstract interpretation", "domsort_ssa!"] |
1.03 (5%) | 0.98 (1%) ✅ |
["inference", "abstract interpretation", "println(::QuoteNode)"] |
1.09 (5%) ❌ | 1.00 (1%) |
["inference", "abstract interpretation", "rand(Float64)"] |
1.03 (5%) | 1.03 (1%) ❌ |
["inference", "abstract interpretation", "sin(42)"] |
1.03 (5%) | 0.98 (1%) ✅ |
["inference", "construct_ssa!"] |
1.01 (5%) | 0.98 (1%) ✅ |
["inference", "domsort_ssa!"] |
1.02 (5%) | 0.99 (1%) ✅ |
["inference", "sin(42)"] |
1.03 (5%) | 0.99 (1%) ✅ |
Here's a list of all the benchmark groups executed by this job:
["inference", "abstract interpretation"]
["inference"]
["inference", "optimization"]
Julia Version 1.9.0-DEV.696
Commit 1493b89a58 (2022-05-30 02:18 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
Ubuntu 20.04.4 LTS
uname: Linux 5.4.0-113-generic #127-Ubuntu SMP Wed May 18 14:30:56 UTC 2022 x86_64 x86_64
CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz:
speed user nice sys idle irq
#1 2989 MHz 17084 s 15 s 3074 s 4745787 s 0 s
#2 2836 MHz 392155 s 27 s 18821 s 4355807 s 0 s
#3 3070 MHz 11999 s 0 s 2392 s 4749311 s 0 s
#4 2683 MHz 8149 s 0 s 2325 s 4752548 s 0 s
#5 3089 MHz 14772 s 0 s 2360 s 4732445 s 0 s
#6 2973 MHz 9942 s 1 s 2327 s 4753532 s 0 s
#7 2935 MHz 11231 s 30 s 2314 s 4752896 s 0 s
#8 3154 MHz 14877 s 1 s 2342 s 4747523 s 0 s
Memory: 31.32082748413086 GB (20666.1640625 MB free)
Uptime: 477027.61 sec
Load Avg: 1.08 1.18 1.34
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-13.0.1 (ORCJIT, haswell)
Threads: 1 on 8 virtual cores
Julia Version 1.9.0-DEV.679
Commit 18bdbbffd7 (2022-05-30 02:09 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
Ubuntu 20.04.4 LTS
uname: Linux 5.4.0-113-generic #127-Ubuntu SMP Wed May 18 14:30:56 UTC 2022 x86_64 x86_64
CPU: Intel(R) Xeon(R) CPU E3-1241 v3 @ 3.50GHz:
speed user nice sys idle irq
#1 3587 MHz 17139 s 15 s 3092 s 4753076 s 0 s
#2 3064 MHz 397983 s 27 s 18900 s 4357274 s 0 s
#3 2886 MHz 12030 s 0 s 2400 s 4756646 s 0 s
#4 3133 MHz 8842 s 0 s 2340 s 4759208 s 0 s
#5 2907 MHz 14807 s 0 s 2368 s 4739768 s 0 s
#6 3066 MHz 9976 s 1 s 2334 s 4760865 s 0 s
#7 3007 MHz 11835 s 30 s 2336 s 4759644 s 0 s
#8 2495 MHz 14928 s 1 s 2349 s 4754838 s 0 s
Memory: 31.32082748413086 GB (20687.171875 MB free)
Uptime: 477765.12 sec
Load Avg: 1.0 1.03 1.15
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-13.0.1 (ORCJIT, haswell)
Threads: 1 on 8 virtual cores