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Fix benchmark ci #91

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Fix benchmark ci #91

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gdalle
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@gdalle gdalle commented Feb 22, 2024

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@gdalle gdalle added the run benchmark Benchmarks are run by CI label Feb 22, 2024
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Benchmark result

Judge result

Benchmark Report for /home/runner/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl

Job Properties

  • Time of benchmarks:
    • Target: 22 Feb 2024 - 19:34
    • Baseline: 22 Feb 2024 - 19:35
  • Package commits:
    • Target: 496b1e
    • Baseline: 5ad5d8
  • Julia commits:
    • Target: 7790d6
    • Baseline: 7790d6
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: OPENBLAS_NUM_THREADS => 1 JULIA_NUM_THREADS => auto
    • Baseline: OPENBLAS_NUM_THREADS => 1 JULIA_NUM_THREADS => auto

Results

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
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 1.57 (5%) ❌ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 0.70 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 0.93 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 0.94 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 0.94 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 0.76 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 0.78 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 0.75 (5%) ✅ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "baum_welch"] 1.16 (5%) ❌ 1.00 (1%)
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 0.89 (5%) ✅ 1.00 (1%)

Benchmark Group List

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

  • ["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1"]
  • ["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]

Julia versioninfo

Target

Julia Version 1.10.1
Commit 7790d6f0641 (2024-02-13 20:41 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.4 LTS
  uname: Linux 6.2.0-1019-azure #19~22.04.1-Ubuntu SMP Wed Jan 10 22:57:03 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1  2445 MHz        838 s          0 s         70 s       2376 s          0 s
       #2  2595 MHz       1010 s          0 s         82 s       2199 s          0 s
       #3  2445 MHz        706 s          0 s        108 s       2466 s          0 s
       #4  3243 MHz        772 s          0 s         94 s       2423 s          0 s
  Memory: 15.60689926147461 GB (14217.78125 MB free)
  Uptime: 331.31 sec
  Load Avg:  2.33  1.1  0.43
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 4 default, 0 interactive, 2 GC (on 4 virtual cores)

Baseline

Julia Version 1.10.1
Commit 7790d6f0641 (2024-02-13 20:41 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.4 LTS
  uname: Linux 6.2.0-1019-azure #19~22.04.1-Ubuntu SMP Wed Jan 10 22:57:03 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1  2445 MHz       1018 s          0 s         73 s       2513 s          0 s
       #2  2591 MHz       1226 s          0 s         86 s       2300 s          0 s
       #3  3243 MHz        825 s          0 s        112 s       2663 s          0 s
       #4  2445 MHz        921 s          0 s         98 s       2592 s          0 s
  Memory: 15.60689926147461 GB (13938.9453125 MB free)
  Uptime: 363.46 sec
  Load Avg:  2.56  1.27  0.51
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 4 default, 0 interactive, 2 GC (on 4 virtual cores)

Target result

Benchmark Report for /home/runner/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl

Job Properties

  • Time of benchmark: 22 Feb 2024 - 19:34
  • Package commit: 496b1e
  • Julia commit: 7790d6
  • Julia command flags: None
  • Environment variables: OPENBLAS_NUM_THREADS => 1 JULIA_NUM_THREADS => auto

Results

Below is a table of this job's results, obtained by running the benchmarks.
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.
An empty cell means that the value was zero.

ID time GC time memory allocations
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 1.823 ms (5%) 5.41 MiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 326.623 μs (5%) 518.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 424.837 μs (5%) 1.26 MiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 1.660 ms (5%) 768.56 KiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 2.040 ms (5%) 18.36 MiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 569.759 μs (5%) 1018.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 765.145 μs (5%) 2.48 MiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 6.209 ms (5%) 1.48 MiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 399.629 μs (5%) 725.38 KiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 140.443 μs (5%) 143.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 217.297 μs (5%) 347.22 KiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 161.091 μs (5%) 206.06 KiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 943.900 μs (5%) 2.42 MiB (1%) 10115
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 514.033 μs (5%) 1.24 MiB (1%) 8028
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 594.485 μs (5%) 1.44 MiB (1%) 8036
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 521.247 μs (5%) 1.30 MiB (1%) 8030
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "baum_welch"] 558.688 μs (5%) 727.66 KiB (1%) 2090
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "forward"] 179.186 μs (5%) 143.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "forward_backward"] 249.869 μs (5%) 347.22 KiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "viterbi"] 206.237 μs (5%) 206.06 KiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 7.722 ms (5%) 870.182 μs 67.57 MiB (1%) 4068
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 1.188 ms (5%) 1.97 MiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 1.715 ms (5%) 4.95 MiB (1%) 36
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 23.885 ms (5%) 2.95 MiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "baum_welch"] 4.692 ms (5%) 15.67 MiB (1%) 16034
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "forward"] 979.957 μs (5%) 2.06 MiB (1%) 2007
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "forward_backward"] 1.298 ms (5%) 5.16 MiB (1%) 3998
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "viterbi"] 21.223 ms (5%) 2.95 MiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 536.686 μs (5%) 1.75 MiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 197.190 μs (5%) 268.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 284.333 μs (5%) 660.09 KiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 479.078 μs (5%) 393.56 KiB (1%) 29

Benchmark Group List

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

  • ["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1"]
  • ["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]

Julia versioninfo

Julia Version 1.10.1
Commit 7790d6f0641 (2024-02-13 20:41 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.4 LTS
  uname: Linux 6.2.0-1019-azure #19~22.04.1-Ubuntu SMP Wed Jan 10 22:57:03 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1  2445 MHz        838 s          0 s         70 s       2376 s          0 s
       #2  2595 MHz       1010 s          0 s         82 s       2199 s          0 s
       #3  2445 MHz        706 s          0 s        108 s       2466 s          0 s
       #4  3243 MHz        772 s          0 s         94 s       2423 s          0 s
  Memory: 15.60689926147461 GB (14217.78125 MB free)
  Uptime: 331.31 sec
  Load Avg:  2.33  1.1  0.43
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 4 default, 0 interactive, 2 GC (on 4 virtual cores)

Baseline result

Benchmark Report for /home/runner/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl

Job Properties

  • Time of benchmark: 22 Feb 2024 - 19:35
  • Package commit: 5ad5d8
  • Julia commit: 7790d6
  • Julia command flags: None
  • Environment variables: OPENBLAS_NUM_THREADS => 1 JULIA_NUM_THREADS => auto

Results

Below is a table of this job's results, obtained by running the benchmarks.
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.
An empty cell means that the value was zero.

ID time GC time memory allocations
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 1.161 ms (5%) 5.41 MiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 321.643 μs (5%) 518.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 421.901 μs (5%) 1.26 MiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 1.659 ms (5%) 768.56 KiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 2.057 ms (5%) 18.36 MiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 563.386 μs (5%) 1018.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 1.086 ms (5%) 2.48 MiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 6.215 ms (5%) 1.48 MiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 401.472 μs (5%) 725.38 KiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 151.384 μs (5%) 143.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 213.120 μs (5%) 347.22 KiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 172.033 μs (5%) 206.06 KiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 1.001 ms (5%) 2.42 MiB (1%) 10115
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 674.754 μs (5%) 1.24 MiB (1%) 8028
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 763.979 μs (5%) 1.44 MiB (1%) 8036
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 691.564 μs (5%) 1.30 MiB (1%) 8030
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "baum_welch"] 557.785 μs (5%) 727.66 KiB (1%) 2090
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "forward"] 175.439 μs (5%) 143.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "forward_backward"] 251.632 μs (5%) 347.22 KiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1", "viterbi"] 199.314 μs (5%) 206.06 KiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 7.742 ms (5%) 878.036 μs 67.57 MiB (1%) 4068
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 1.156 ms (5%) 1.97 MiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 1.703 ms (5%) 4.95 MiB (1%) 36
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 23.917 ms (5%) 2.95 MiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "baum_welch"] 4.045 ms (5%) 15.67 MiB (1%) 16034
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "forward"] 981.139 μs (5%) 2.06 MiB (1%) 2007
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "forward_backward"] 1.287 ms (5%) 5.16 MiB (1%) 3998
["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0", "viterbi"] 21.164 ms (5%) 2.95 MiB (1%) 29
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "baum_welch"] 605.894 μs (5%) 1.75 MiB (1%) 2066
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward"] 196.808 μs (5%) 268.45 KiB (1%) 27
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "forward_backward"] 280.836 μs (5%) 660.09 KiB (1%) 35
["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0", "viterbi"] 481.032 μs (5%) 393.56 KiB (1%) 29

Benchmark Group List

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

  • ["HiddenMarkovModels.jl", "nb_states 16 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 32 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 4 obs_dim 10 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 1"]
  • ["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 64 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 1 custom_dist 0"]
  • ["HiddenMarkovModels.jl", "nb_states 8 obs_dim 1 seq_length 100 nb_seqs 20 bw_iter 1 sparse 0 custom_dist 0"]

Julia versioninfo

Julia Version 1.10.1
Commit 7790d6f0641 (2024-02-13 20:41 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.4 LTS
  uname: Linux 6.2.0-1019-azure #19~22.04.1-Ubuntu SMP Wed Jan 10 22:57:03 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1  2445 MHz       1018 s          0 s         73 s       2513 s          0 s
       #2  2591 MHz       1226 s          0 s         86 s       2300 s          0 s
       #3  3243 MHz        825 s          0 s        112 s       2663 s          0 s
       #4  2445 MHz        921 s          0 s         98 s       2592 s          0 s
  Memory: 15.60689926147461 GB (13938.9453125 MB free)
  Uptime: 363.46 sec
  Load Avg:  2.56  1.27  0.51
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 4 default, 0 interactive, 2 GC (on 4 virtual cores)

Runtime information

Runtime Info
BLAS #threads 2
BLAS.vendor() lbt
Sys.CPU_THREADS 4

lscpu output:

Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      48 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             4
On-line CPU(s) list:                0-3
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 7763 64-Core Processor
CPU family:                         25
Model:                              1
Thread(s) per core:                 2
Core(s) per socket:                 2
Socket(s):                          1
Stepping:                           1
BogoMIPS:                           4890.86
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext invpcid_single vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                     AMD-V
Hypervisor vendor:                  Microsoft
Virtualization type:                full
L1d cache:                          64 KiB (2 instances)
L1i cache:                          64 KiB (2 instances)
L2 cache:                           1 MiB (2 instances)
L3 cache:                           32 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-3
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Not affected
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Mitigation; safe RET, no microcode
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Cpu Property Value
Brand AMD EPYC 7763 64-Core Processor
Vendor :AMD
Architecture :Unknown
Model Family: 0xaf, Model: 0x01, Stepping: 0x01, Type: 0x00
Cores 16 physical cores, 16 logical cores (on executing CPU)
No Hyperthreading hardware capability detected
Clock Frequencies Not supported by CPU
Data Cache Level 1:3 : (32, 512, 32768) kbytes
64 byte cache line size
Address Size 48 bits virtual, 48 bits physical
SIMD 256 bit = 32 byte max. SIMD vector size
Time Stamp Counter TSC is accessible via rdtsc
TSC runs at constant rate (invariant from clock frequency)
Perf. Monitoring Performance Monitoring Counters (PMC) are not supported
Hypervisor Yes, Microsoft

@gdalle gdalle closed this Feb 22, 2024
@gdalle gdalle deleted the testbench branch February 22, 2024 19:38
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