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net: Initialize return value in gro_cells_receive #188

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Pull request for series with
subject: net: Initialize return value in gro_cells_receive
version: 1
url: https://patchwork.kernel.org/project/bpf/list/?series=360465

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Master branch: 67ed375
series: https://patchwork.kernel.org/project/bpf/list/?series=360465
version: 1

Pull request is NOT updated. Failed to apply https://patchwork.kernel.org/project/bpf/list/?series=360465
error message:

Cmd('git') failed due to: exit code(128)
  cmdline: git am -3
  stdout: 'Applying: net: Initialize return value in gro_cells_receive
Patch failed at 0001 net: Initialize return value in gro_cells_receive
When you have resolved this problem, run "git am --continue".
If you prefer to skip this patch, run "git am --skip" instead.
To restore the original branch and stop patching, run "git am --abort".'
  stderr: 'error: corrupt patch at line 6
error: could not build fake ancestor
hint: Use 'git am --show-current-patch' to see the failed patch'

conflict:


@kernel-patches-bot kernel-patches-bot deleted the series/360465=>bpf-next branch October 7, 2020 01:45
kernel-patches-bot pushed a commit that referenced this pull request Nov 18, 2021
In this patch -
1) Add a new prog "for_each_helper" which tests the basic functionality of
the bpf_for_each helper.

2) Add pyperf600_foreach and strobemeta_foreach to test the performance
of using bpf_for_each instead of a for loop

The results of pyperf600 and strobemeta are as follows:

~strobemeta~

Baseline
    verification time 6808200 usec
    stack depth 496
    processed 592132 insns (limit 1000000) max_states_per_insn 14
    total_states 16018 peak_states 13684 mark_read 3132
    #188 verif_scale_strobemeta:OK (unrolled loop)

Using bpf_for_each
    verification time 31589 usec
    stack depth 96+408
    processed 1630 insns (limit 1000000) max_states_per_insn 4
    total_states 107 peak_states 107 mark_read 60
    #189 verif_scale_strobemeta_foreach:OK

~pyperf600~

Baseline
    verification time 29702486 usec
    stack depth 368
    processed 626838 insns (limit 1000000) max_states_per_insn 7
    total_states 30368 peak_states 30279 mark_read 748
    #182 verif_scale_pyperf600:OK (unrolled loop)

Using bpf_for_each
    verification time 148488 usec
    stack depth 320+40
    processed 10518 insns (limit 1000000) max_states_per_insn 10
    total_states 705 peak_states 517 mark_read 38
    #183 verif_scale_pyperf600_foreach:OK

Using the bpf_for_each helper led to approximately a 100% decrease
in the verification time and in the number of instructions.

Signed-off-by: Joanne Koong <joannekoong@fb.com>
kernel-patches-bot pushed a commit that referenced this pull request Nov 18, 2021
In this patch -
1) Add a new prog "for_each_helper" which tests the basic functionality of
the bpf_for_each helper.

2) Add pyperf600_foreach and strobemeta_foreach to test the performance
of using bpf_for_each instead of a for loop

The results of pyperf600 and strobemeta are as follows:

~strobemeta~

Baseline
    verification time 6808200 usec
    stack depth 496
    processed 592132 insns (limit 1000000) max_states_per_insn 14
    total_states 16018 peak_states 13684 mark_read 3132
    #188 verif_scale_strobemeta:OK (unrolled loop)

Using bpf_for_each
    verification time 31589 usec
    stack depth 96+408
    processed 1630 insns (limit 1000000) max_states_per_insn 4
    total_states 107 peak_states 107 mark_read 60
    #189 verif_scale_strobemeta_foreach:OK

~pyperf600~

Baseline
    verification time 29702486 usec
    stack depth 368
    processed 626838 insns (limit 1000000) max_states_per_insn 7
    total_states 30368 peak_states 30279 mark_read 748
    #182 verif_scale_pyperf600:OK (unrolled loop)

Using bpf_for_each
    verification time 148488 usec
    stack depth 320+40
    processed 10518 insns (limit 1000000) max_states_per_insn 10
    total_states 705 peak_states 517 mark_read 38
    #183 verif_scale_pyperf600_foreach:OK

Using the bpf_for_each helper led to approximately a 100% decrease
in the verification time and in the number of instructions.

Signed-off-by: Joanne Koong <joannekoong@fb.com>
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