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authorMaciek Konstantynowicz <mkonstan@cisco.com>2019-05-10 11:05:15 +0100
committerTibor Frank <tifrank@cisco.com>2019-05-10 10:32:35 +0000
commitb4b1c9bf381c1570a15651dfb1997a657cbbcc92 (patch)
tree023625467d35aa1d9097d3dbaa0154582fe8324a /docs/report
parente79a1eed9da5aa88e783d442743025b3fc73ba77 (diff)
report: edits of methodology mlrsearch section
Change-Id: I80b4f8223d2991e258ab422c447bdc09d92c9e9c Signed-off-by: Maciek Konstantynowicz <mkonstan@cisco.com>
Diffstat (limited to 'docs/report')
-rw-r--r--docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst8
-rw-r--r--docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst286
2 files changed, 29 insertions, 265 deletions
diff --git a/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst b/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst
index 762a7c2675..3d33b22b55 100644
--- a/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst
+++ b/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst
@@ -22,10 +22,10 @@ Description
Multiple Loss Ratio search (MLRsearch) tests discover multiple packet
throughput rates in a single search, reducing the overall test execution
-time compared to a binary search. Each rate associated with a distinct
-Packet Loss Ratio (PLR) criteria. In FD.io CSIT two throughput rates are
-discovered: Non-Drop Rate (NDR, with zero packet loss, PLR=0) and
-Partial Drop Rate (PDR, with PLR<0.5%). MLRsearch is compliant with
+time compared to a binary search. Each rate is associated with a
+distinct Packet Loss Ratio (PLR) criteria. In FD.io CSIT two throughput
+rates are discovered: Non-Drop Rate (NDR, with zero packet loss, PLR=0)
+and Partial Drop Rate (PDR, with PLR<0.5%). MLRsearch is compliant with
:rfc:`2544`.
Usage
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 6c2adfcd06..acc974841d 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
@@ -3,287 +3,51 @@
MLRsearch Tests
---------------
+Overview
+~~~~~~~~
+
Multiple Loss Rate search (MLRsearch) tests use new search algorithm
implemented in FD.io CSIT project. MLRsearch discovers multiple packet
throughput rates in a single search, with each rate associated with a
-distinct Packet Loss Ratio (PLR) criteria. MLRsearch is being
-standardized in IETF with `draft-vpolak-mkonstan-mlrsearch-XX
-<https://tools.ietf.org/html/draft-vpolak-mkonstan-mlrsearch-00>`_.
+different Packet Loss Ratio (PLR) criteria.
Two throughput measurements used 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). MLRsearch
-discovers NDR and PDR in a single pass reducing required execution time
-compared to separate binary searches for NDR and PDR. MLRsearch reduces
-execution time 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 shorter overall search
-execution time when compared to a standard NDR/PDR binary search,
-while guaranteeing the same or similar results.
+loss rate not greater than the configured non-zero PLR).
-If needed, MLRsearch can be easily adopted to discover more throughput rates
-with different pre-defined PLRs.
+MLRsearch discovers NDR and PDR in a single pass reducing required time
+duration compared to separate binary searches for NDR and PDR. 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
+shorter overall execution time when compared to standard NDR/PDR binary
+search, while guaranteeing similar results.
+
+If needed, MLRsearch can be easily adopted to discover more throughput
+rates with different pre-defined PLRs.
.. 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.
-Overview
-~~~~~~~~
-
-The main properties of MLRsearch:
-
-- MLRsearch is a duration aware multi-phase multi-rate search algorithm.
-
- - Initial phase determines promising starting interval for the search.
- - Intermediate phases progress towards defined final search criteria.
- - Final phase executes measurements according to the final search
- criteria.
-
-- *Initial phase*:
-
- - Uses link rate as a starting transmit rate and discovers the Maximum
- Receive Rate (MRR) used as an input to the first intermediate phase.
-
-- *Intermediate phases*:
-
- - Start with initial trial duration (in the first phase) and converge
- geometrically towards the final trial duration (in the final phase).
- - Track two values for NDR and two for PDR.
-
- - The values are called (NDR or PDR) lower_bound and upper_bound.
- - Each value comes from a specific trial measurement
- (most recent for that transmit rate),
- and as such the value is associated with that measurement's duration and
- loss.
- - A bound can be invalid, for example if NDR lower_bound
- has been measured with nonzero loss.
- - Invalid bounds are not real boundaries for the searched value,
- but are needed to track interval widths.
- - Valid bounds are real boundaries for the searched value.
- - Each non-initial phase ends with all bounds valid.
-
- - Start with a large (lower_bound, upper_bound) interval width and
- geometrically converge towards the width goal (measurement resolution)
- of the phase. Each phase halves the previous width goal.
- - Use internal and external searches:
-
- - External search - measures at transmit rates outside the (lower_bound,
- upper_bound) interval. Activated when a bound is invalid,
- to search for a new valid bound by doubling the interval width.
- It is a variant of `exponential search`_.
- - Internal search - `binary search`_, measures at transmit rates within the
- (lower_bound, upper_bound) valid interval, halving the interval width.
-
-- *Final phase* is executed with the final test trial duration, and the final
- width goal that determines resolution of the overall search.
- Intermediate phases together with the final phase are called non-initial
- phases.
-
-The main benefits of MLRsearch vs. binary search include:
-
-- In general MLRsearch is likely to execute more search trials overall, but
- less trials at a set final duration.
-- In well behaving cases it greatly reduces (>50%) the overall duration
- compared to a single PDR (or NDR) binary search duration,
- while finding multiple drop rates.
-- In all cases MLRsearch yields the same or similar results to binary search.
-- Note: both binary search and MLRsearch are susceptible to reporting
- non-repeatable results across multiple runs for very bad behaving
- cases.
-
-Caveats:
-
-- Worst case MLRsearch can take longer than a binary search e.g. in case of
- drastic changes in behaviour for trials at varying durations.
-
Search Implementation
~~~~~~~~~~~~~~~~~~~~~
-Following is a brief description of the current MLRsearch
-implementation in FD.io CSIT.
-
-Input Parameters
-````````````````
-
-#. *maximum_transmit_rate* - maximum packet transmit rate to be used by
- external traffic generator, limited by either the actual Ethernet
- link rate or traffic generator NIC model capabilities. Sample
- defaults: 2 * 14.88 Mpps for 64B 10GE link rate,
- 2 * 18.75 Mpps for 64B 40GE NIC maximum rate.
-#. *minimum_transmit_rate* - minimum packet transmit rate to be used for
- measurements. MLRsearch fails if lower transmit rate needs to be
- used to meet search criteria. Default: 2 * 10 kpps (could be higher).
-#. *final_trial_duration* - required trial duration for final rate
- measurements. Default: 30 sec.
-#. *initial_trial_duration* - trial duration for initial MLRsearch phase.
- Default: 1 sec.
-#. *final_relative_width* - required measurement resolution expressed as
- (lower_bound, upper_bound) interval width relative to upper_bound.
- Default: 0.5%.
-#. *packet_loss_ratio* - maximum acceptable PLR search criteria for
- PDR measurements. Default: 0.5%.
-#. *number_of_intermediate_phases* - number of phases between the initial
- phase and the final phase. Impacts the overall MLRsearch duration.
- Less phases are required for well behaving cases, more phases
- may be needed to reduce the overall search duration for worse behaving
- cases.
- Default (2). (Value chosen based on limited experimentation to date.
- More experimentation needed to arrive to clearer guidelines.)
-
-Initial Phase
-`````````````
-
-1. First trial measures at maximum rate and discovers MRR.
-
- a. *in*: trial_duration = initial_trial_duration.
- b. *in*: offered_transmit_rate = maximum_transmit_rate.
- c. *do*: single trial.
- d. *out*: measured loss ratio.
- e. *out*: mrr = measured receive rate.
-
-2. Second trial measures at MRR and discovers MRR2.
-
- a. *in*: trial_duration = initial_trial_duration.
- b. *in*: offered_transmit_rate = MRR.
- c. *do*: single trial.
- d. *out*: measured loss ratio.
- e. *out*: mrr2 = measured receive rate.
-
-3. Third trial measures at MRR2.
+Detailed description of the MLRsearch algorithm is included in the IETF
+draft `draft-vpolak-mkonstan-mlrsearch
+<https://tools.ietf.org/html/draft-vpolak-mkonstan-bmwg-mlrsearch>`_
+that is in the process of being standardized in the IETF Benchmarking
+Methodology Working Group (BMWG).
- a. *in*: trial_duration = initial_trial_duration.
- b. *in*: offered_transmit_rate = MRR2.
- c. *do*: single trial.
- d. *out*: measured loss ratio.
-
-Non-initial Phases
-``````````````````
-
-1. Main loop:
-
- a. *in*: trial_duration for the current phase.
- Set to initial_trial_duration for the first intermediate phase;
- to final_trial_duration for the final phase;
- or to the element of interpolating geometric sequence
- for other intermediate phases.
- For example with two intermediate phases, trial_duration
- of the second intermediate phase is the geometric average
- of initial_strial_duration and final_trial_duration.
- b. *in*: relative_width_goal for the current phase.
- Set to final_relative_width for the final phase;
- doubled for each preceding phase.
- For example with two intermediate phases,
- the first intermediate phase uses quadruple of final_relative_width
- and the second intermediate phase uses double of final_relative_width.
- c. *in*: ndr_interval, pdr_interval from the previous main loop iteration
- or the previous phase.
- If the previous phase is the initial phase, both intervals have
- lower_bound = MRR2, uper_bound = MRR.
- Note that the initial phase is likely to create intervals with invalid
- bounds.
- d. *do*: According to the procedure described in point 2,
- either exit the phase (by jumping to 1.g.),
- or prepare new transmit rate to measure with.
- e. *do*: Perform the trial measurement at the new transmit rate
- and trial_duration, compute its loss ratio.
- f. *do*: Update the bounds of both intervals, based on the new measurement.
- The actual update rules are numerous, as NDR external search
- can affect PDR interval and vice versa, but the result
- agrees with rules of both internal and external search.
- For example, any new measurement below an invalid lower_bound
- becomes the new lower_bound, while the old measurement
- (previously acting as the invalid lower_bound)
- becomes a new and valid upper_bound.
- Go to next iteration (1.c.), taking the updated intervals as new input.
- g. *out*: current ndr_interval and pdr_interval.
- In the final phase this is also considered
- to be the result of the whole search.
- For other phases, the next phase loop is started
- with the current results as an input.
-
-2. New transmit rate (or exit) calculation (for 1.d.):
-
- - If there is an invalid bound then prepare for external search:
-
- - *If* the most recent measurement at NDR lower_bound transmit rate
- had the loss higher than zero, then
- the new transmit rate is NDR lower_bound
- decreased by two NDR interval widths.
- - Else, *if* the most recent measurement at PDR lower_bound
- transmit rate had the loss higher than PLR, then
- the new transmit rate is PDR lower_bound
- decreased by two PDR interval widths.
- - Else, *if* the most recent measurement at NDR upper_bound
- transmit rate had no loss, then
- the new transmit rate is NDR upper_bound
- increased by two NDR interval widths.
- - Else, *if* the most recent measurement at PDR upper_bound
- transmit rate had the loss lower or equal to PLR, then
- the new transmit rate is PDR upper_bound
- increased by two PDR interval widths.
- - If interval width is higher than the current phase goal:
-
- - Else, *if* NDR interval does not meet the current phase width goal,
- prepare for internal search. The new transmit rate is
- (NDR lower bound + NDR upper bound) / 2.
- - Else, *if* PDR interval does not meet the current phase width goal,
- prepare for internal search. The new transmit rate is
- (PDR lower bound + PDR upper bound) / 2.
- - Else, *if* some bound has still only been measured at a lower duration,
- prepare to re-measure at the current duration (and the same transmit
- rate). The order of priorities is:
-
- - NDR lower_bound,
- - PDR lower_bound,
- - NDR upper_bound,
- - PDR upper_bound.
- - *Else*, do not prepare any new rate, to exit the phase.
- This ensures that at the end of each non-initial phase
- all intervals are valid, narrow enough, and measured
- at current phase trial duration.
+MLRsearch is also available as a `PyPI (Python Package Index) library
+<https://pypi.org/project/MLRsearch/>`_.
Implementation Deviations
~~~~~~~~~~~~~~~~~~~~~~~~~
-This document so far has been describing a simplified version of MLRsearch
-algorithm. The full algorithm as implemented contains additional logic,
-which makes some of the details (but not general ideas) above incorrect.
-Here is a short description of the additional logic as a list of principles,
-explaining their main differences from (or additions to) the simplified
-description,but without detailing their mutual interaction.
-
-1. *Logarithmic transmit rate.*
- In order to better fit the relative width goal,
- the interval doubling and halving is done differently.
- For example, the middle of 2 and 8 is 4, not 5.
-2. *Optimistic maximum rate.*
- The increased rate is never higher than the maximum rate.
- Upper bound at that rate is always considered valid.
-3. *Pessimistic minimum rate.*
- The decreased rate is never lower than the minimum rate.
- If a lower bound at that rate is invalid,
- a phase stops refining the interval further (until it gets re-measured).
-4. *Conservative interval updates.*
- Measurements above current upper bound never update a valid upper bound,
- even if drop ratio is low.
- Measurements below current lower bound always update any lower bound
- if drop ratio is high.
-5. *Ensure sufficient interval width.*
- Narrow intervals make external search take more time to find a valid bound.
- If the new transmit increased or decreased rate would result in width
- less than the current goal, increase/decrease more.
- This can happen if the measurement for the other interval
- makes the current interval too narrow.
- Similarly, take care the measurements in the initial phase
- create wide enough interval.
-6. *Timeout for bad cases.*
- The worst case for MLRsearch is when each phase converges to intervals
- way different than the results of the previous phase.
- Rather than suffer total search time several times larger
- than pure binary search, the implemented tests fail themselves
- when the search takes too long (given by argument *timeout*).
+FD.io CSIT implementation of MLRsearch so far is fully based on the -01
+version of the `draft-vpolak-mkonstan-mlrsearch-01
+<https://tools.ietf.org/html/draft-vpolak-mkonstan-bmwg-mlrsearch-01>`_.
.. _binary search: https://en.wikipedia.org/wiki/Binary_search
.. _exponential search: https://en.wikipedia.org/wiki/Exponential_search