From 20b64f8ed040b3b25c37d71fc8feed28b9a557fd Mon Sep 17 00:00:00 2001 From: Vratko Polak Date: Thu, 10 Nov 2022 15:17:08 +0100 Subject: fix(report): update MLRsearch methodology Change-Id: I0f68c1569a7300434c7142c3856e7641d7cbf934 Signed-off-by: Vratko Polak --- .../methodology_mlrsearch_tests.rst | 74 ++++++++++++++++------ 1 file changed, 56 insertions(+), 18 deletions(-) (limited to 'docs/report') diff --git a/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst b/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst index f834ca3e1b..1f0da11f49 100644 --- a/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst +++ b/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst @@ -6,17 +6,16 @@ MLRsearch Tests Overview ~~~~~~~~ -Multiple Loss Rate search (MLRsearch) tests use new search algorithm -implemented in FD.io CSIT project. MLRsearch discovers any number of packet -throughput rates in a single search, with each rate associated with a -different Packet Loss Ratio (PLR) criteria. +Multiple Loss Ratio search (MLRsearch) tests use an optimized search algorithm +implemented in FD.io CSIT project. MLRsearch discovers any number of +loss ratio loads in a single search. -Two throughput rates of interest in FD.io CSIT are Non-Drop Rate (NDR, -with zero packet loss, PLR=0) and Partial Drop Rate (PDR, with packet -loss rate not greater than the configured non-zero PLR, currently 0.5%). +Two loss ratio goals are of interest in FD.io CSIT, leading to Non-Drop Rate +(NDR, loss ratio goal is exact zero) and Partial Drop Rate +(PDR, non-zero loss ratio goal, currently 0.5%). -MLRsearch discovers all the rates in a single pass, reducing required time -duration compared to separate `binary search`_ for each rate. Overall +MLRsearch discovers all the loads in a single pass, reducing required time +duration compared to separate `binary search`_es for each rate. Overall search time is reduced even further by relying on shorter trial durations of intermediate steps, with only the final measurements conducted at the specified final trial duration. This results in the @@ -25,26 +24,65 @@ search, while guaranteeing similar results. .. Note:: All throughput rates are *always* bi-directional aggregates of two equal (symmetric) uni-directional packet rates - received and reported by an external traffic generator. + received and reported by an external traffic generator, + unless the test specifically requires unidirectional traffic. Search Implementation ~~~~~~~~~~~~~~~~~~~~~ Detailed description of the MLRsearch algorithm is included in the IETF -draft `draft-ietf-bmwg-mlrsearch-01 -`_ +draft `draft-ietf-bmwg-mlrsearch-02 +`_ that is in the process of being standardized in the IETF Benchmarking Methodology Working Group (BMWG). +(Newer version is published in IETF, describing improvements not yet used +in CSIT production.) MLRsearch is also available as a `PyPI (Python Package Index) library `_. -Implementation Deviations -~~~~~~~~~~~~~~~~~~~~~~~~~ +Algorithm highlights +~~~~~~~~~~~~~~~~~~~~ -FD.io CSIT implementation of MLRsearch is currently fully based on the -01` -version of the `draft-ietf-bmwg-mlrsearch -`_, -the PyPI version is slightly older. +MRR and receive rate at MRR load are used as initial guesses for the search. + +All previously measured trials (except the very first one which can act +as a warm-up) are taken into consideration, unless superseded +by a trial at the same load but higher duration. + +For every loss ratio goal, tightest upper and lower bound +(from results of large enough trial duration) form an interval. +Exit condition is given by that interval reaching low enough relative width. +Small enough width is achieved by bisecting the current interval. +The bisection can be uneven, to save measurements based on information theory. + +Switching to higher trial duration generally requires a re-measure +at a load from previous trial duration. +When the re-measurement does not confirm previous bound classification +(e.g. tightest lower bound at shorter trial duration becomes +a newest tightest upper bound upon re-measurement), +external search is used to find close enough bound of the lost type. +External search is a generalization of the first stage of `exponential search`_. + +Shorter trial durations use double width goal, +because one bisection is always safe before risking external search. + +Within an iteration for a specific trial duration, smaller loss ratios (NDR) +are narrowed down first before search continues with higher loss ratios (PDR). + +Other heuristics are there, aimed to prevent unneccessarily narrow intervals, +and to handle corner cases around min and max load. + +Deviations from RFC 2544 +~~~~~~~~~~~~~~~~~~~~~~~~ + +CSIT does not have any explicit wait times before and after trial traffic. + +Small differences between intended and offered load are tolerated, +mainly due to various time overheads preventing precise measurement +of the traffic duration (and TRex can sometimes suffer from duration stretching). + +The final trial duration is only 30s (10s for reconf tests). .. _binary search: https://en.wikipedia.org/wiki/Binary_search +.. _exponential search: https://en.wikipedia.org/wiki/Exponential_search -- cgit 1.2.3-korg