[LibreQoS] In BPF pping - so far

Wed Oct 19 09:44:20 EDT 2022

Hey,

Testing the current version (
https://github.com/thebracket/cpumap-pping-hackjob ), it's doing better
than I hoped. This build has shared (not per-cpu) maps, and a userspace
daemon (xdp_pping) to extract and reset stats.

My testing environment has grown a bit:
* ShaperVM - running Ubuntu Server and LibreQoS, with the new
cpumap-pping-hackjob version of xdp-cpumap.
* ExtTest - running Ubuntu Server, set as 10.64.1.1. Hosts an iperf server.
* ClientInt1 - running Ubuntu Server (minimal), set as 10.64.1.2. Hosts
iperf client.
* ClientInt2 - running Ubuntu Server (minimal), set as 10.64.1.3. Hosts
iperf client.

ClientInt1, ClientInt2 and one interface (LAN facing) of ShaperVM are on a
virtual switch.
ExtTest and the other interface (WAN facing) of ShaperVM are on a different
virtual switch.

These are all on a host machine running Windows 11, a core i7 12th gen, 32
Gb RAM and fast SSD setup.

TEST 1: DUAL STREAMS, LOW THROUGHPUT

For this test, LibreQoS is configured:
* Two APs, each with 5gbit/s max.
* 100.64.1.2 and 100.64.1.3 setup as CPEs, each limited to about 100mbit/s.
They map to 1:5 and 2:5 respectively (separate CPUs).
* Set to use Cake

On each client, roughly simultaneously run: iperf -c 100.64.1.1 -t 500 (for
a long run). Running xdp_pping yields correct results:

[
{"tc":"1:5", "avg" : 4, "min" : 3, "max" : 5, "samples" : 11},
{"tc":"2:5", "avg" : 4, "min" : 3, "max" : 5, "samples" : 11},
{}]

Or when I waited a while to gather/reset:

[
{"tc":"1:5", "avg" : 4, "min" : 3, "max" : 6, "samples" : 60},
{"tc":"2:5", "avg" : 4, "min" : 3, "max" : 5, "samples" : 60},
{}]

The ShaperVM shows no errors, just periodic logging that it is recording
data.  CPU is about 2-3% on two CPUs, zero on the others (as expected).

After 500 seconds of continual iperfing, each client reported a throughput
of 104 Mbit/sec and 6.06 GBytes of data transmitted.

So for smaller streams, I'd call this a success.

TEST 2: DUAL STREAMS, HIGH THROUGHPUT

For this test, LibreQoS is configured:
* Two APs, each with 5gb/s max.
* 100.64.1.2 and 100.64.1.3 setup as CPEs, each limited to 5Gbit/s! Mapped
to 1:5 and 2:5 respectively (separate CPUs).

Run iperfc -c 100.64.1.1 -t 500 on each client at the same time.

xdp_pping shows results, too:

[
{"tc":"1:5", "avg" : 4, "min" : 1, "max" : 7, "samples" : 58},
{"tc":"2:5", "avg" : 7, "min" : 3, "max" : 11, "samples" : 58},
{}]

[
{"tc":"1:5", "avg" : 5, "min" : 4, "max" : 8, "samples" : 13},
{"tc":"2:5", "avg" : 8, "min" : 7, "max" : 10, "samples" : 13},
{}]

The ShaperVM shows two CPUs pegging between 70 and 90 percent.

After 500 seconds of continual iperfing, each client reported a throughput
of 2.72 Gbits/sec (158 GBytes) and 3.89 Gbits/sec and 226 GBytes.

Maxing out HyperV like this is inducing a bit of latency (which is to be
expected), but it's not bad. I also forgot to disable hyperthreading, and
looking at the host performance it is sometimes running the second virtual
CPU on an underpowered "fake" CPU.

So for two large streams, I think we're doing pretty well also!

TEST 3: DUAL STREAMS, SINGLE CPU

This test is designed to try and blow things up. It's the same as test 2,
but both CPEs are set to the same CPU (1), using TC handles 1:5 and 1:6.

ShaperVM CPU1 maxed out in the high 90s, the other CPUs were idle. The
pping stats start to show a bit of degradation in performance for pounding
it so hard:

[
{"tc":"1:6", "avg" : 10, "min" : 9, "max" : 19, "samples" : 24},
{"tc":"1:5", "avg" : 10, "min" : 8, "max" : 18, "samples" : 24},
{}]

For whatever reason, it smoothed out over time:

[
{"tc":"1:6", "avg" : 10, "min" : 9, "max" : 12, "samples" : 50},
{"tc":"1:5", "avg" : 10, "min" : 8, "max" : 13, "samples" : 50},
{}]

Surprisingly (to me), I didn't encounter errors. Each client received 2.22
Gbit/s performance, over 129 Gbytes of data.

TEST 4: DUAL STREAMS, 50 SUB-STREAMS

This test is also designed to break things. Same as test 3, but using iperf
-c 100.64.1.1 -P 50 -t 120 - 50 substreams, to try and really tax the flow
tracking. (Shorter time window because I really wanted to go and find
coffee)

ShaperVM CPU sat at around 80-97%, tending towards 97%. pping results show
that this torture test is worsening performance, and there's always lots of
samples in the buffer:

[
{"tc":"1:6", "avg" : 23, "min" : 19, "max" : 27, "samples" : 49},
{"tc":"1:5", "avg" : 24, "min" : 19, "max" : 27, "samples" : 49},
{}]

This test also ran better than I expected. You can definitely see some
latency creeping in as I make the system work hard. Each VM showed around
2.4 Gbit/s in total performance at the end of the iperf session. There's
definitely some latency creeping in, which is expected - but I'm not sure I
expected quite that much.

WHAT'S NEXT & CONCLUSION

I noticed that I forgot to turn off efficient power management on my VMs
and host, and left Hyperthreading on by mistake. So that hurts overall
performance.

The base system seems to be working pretty solidly, at least for small
tests.Next up, I'll be removing extraneous debug reporting code, removing
some code paths that don't do anything but report, and looking for any
small optimization opportunities. I'll then re-run these tests. Once that's
done, I hope to find a maintenance window on my WISP and try it with actual
traffic.

I also need to re-run these tests without the pping system to provide some
before/after analysis.

On Tue, Oct 18, 2022 at 1:01 PM Herbert Wolverson <herberticus at gmail.com>
wrote:

> It's probably not entirely thread-safe right now (ran into some issues
> reading per_cpu maps back from userspace; hopefully, I'll get that figured
> out) - but the commits I just pushed have it basically working on
> single-stream testing. :-)
>
> Setup cpumap as usual, and periodically run xdp-pping. This gives you
> per-connection RTT information in JSON:
>
> [
> {"tc":"1:5", "avg" : 5, "min" : 5, "max" : 5, "samples" : 1},
> {}]
>
> (With the extra {} because I'm not tracking the tail and haven't done
> comma removal). The tool also empties the various maps used to gather data,
> acting as a "reset" point. There's a max of 60 samples per queue, in a
> ringbuffer setup (so newest will start to overwrite the oldest).
>
> I'll start trying to test on a larger scale now.
>
> On Mon, Oct 17, 2022 at 3:34 PM Robert Chacón <
> robert.chacon at jackrabbitwireless.com> wrote:
>
>> Hey Herbert,
>>
>> Fantastic work! Super exciting to see this coming together, especially so
>> quickly.
>> I'll test it soon.
>> I understand and agree with your decision to omit certain features (ICMP
>> tracking,DNS tracking, etc) to optimize performance for our use case. Like
>> you said, in order to merge the functionality without a performance hit,
>> merging them is sort of the only way right now. Otherwise there would be a
>> lot of redundancy and lost throughput for an ISP's use. Though hopefully
>> long term there will be a way to keep all projects working independently
>> but interoperably with a plugin system of some kind.
>>
>> By the way, I'm making some headway on LibreQoS v1.3. Focusing on
>> optimizations for high sub counts (8000+ subs) as well as stateful changes
>> to the queue structure.
>> I'm working to set up a physical lab to test high throughput and high
>> client count scenarios.
>> When testing beyond ~32,000 filters we get "no space left on device" from
>> xdp-cpumap-tc, which I think relates to the bpf map size limitation you
>> mentioned. Maybe in the coming months we can take a look at that.
>>
>> Anyway great work on the cpumap-pping program! Excited to see more on
>> this.
>>
>> Thanks,
>> Robert
>>
>> On Mon, Oct 17, 2022 at 12:45 PM Herbert Wolverson via LibreQoS <
>> libreqos at lists.bufferbloat.net> wrote:
>>
>>> Hey,
>>>
>>> My current (unfinished) progress on this is now available here:
>>> https://github.com/thebracket/cpumap-pping-hackjob
>>>
>>> I mean it about the warnings, this isn't at all stable, debugged - and
>>> can't promise that it won't unleash the nasal demons
>>> (to use a popular C++ phrase). The name is descriptive! ;-)
>>>
>>> With that said, I'm pretty happy so far:
>>>
>>> * It runs only on the classifier - which xdp-cpumap-tc has nicely
>>> shunted onto a dedicated CPU. It has to run on both
>>>   the inbound and outbound classifiers, since otherwise it would only
>>> see half the conversation.
>>> * It does assume that your ingress and egress CPUs are mapped to the
>>> same interface; I do that anyway in BracketQoS. Not doing
>>>   that opens up a potential world of pain, since writes to the shared
>>> maps would require a locking scheme. Too much locking, and you lose all of
>>> the benefit of using multiple CPUs to begin with.
>>> * It is pretty wasteful of RAM, but most of the shaper systems I've
>>> worked with have lots of it.
>>> * I've been gradually removing features that I don't want for
>>> BracketQoS. A hypothetical future "useful to everyone" version wouldn't do
>>> that.
>>> * Rate limiting is working, but I removed the requirement for a shared
>>> configuration provided from userland - so right now it's always set to
>>> report at 1 second intervals per stream.
>>>
>>> My testbed is currently 3 Hyper-V VMs - a simple "client" and "world",
>>> and a "shaper" VM in between running a slightly hacked-up LibreQoS.
>>> iperf from "client" to "world" (with Libre set to allow 10gbit/s max,
>>> via a cake/HTB queue setup) is around 5 gbit/s at present, on my
>>> test PC (the host is a core i7, 12th gen, 12 cores - 64gb RAM and fast
>>> SSDs)
>>>
>>> Output currently consists of debug messages reading:
>>>   cpumap/0/map:4-1371    [000] D..2.   515.399222: bpf_trace_printk:
>>> (tc) Flow open event
>>>   cpumap/0/map:4-1371    [000] D..2.   515.399239: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 374696
>>>   cpumap/0/map:4-1371    [000] D..2.   515.399466: bpf_trace_printk:
>>> (tc) Flow open event
>>>   cpumap/0/map:4-1371    [000] D..2.   515.399475: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 247069
>>>   cpumap/0/map:4-1371    [000] D..2.   516.405151: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 5217155
>>>   cpumap/0/map:4-1371    [000] D..2.   517.405248: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 4515394
>>>   cpumap/0/map:4-1371    [000] D..2.   518.406117: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 4481289
>>>   cpumap/0/map:4-1371    [000] D..2.   519.406255: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 4255268
>>>   cpumap/0/map:4-1371    [000] D..2.   520.407864: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 5249493
>>>   cpumap/0/map:4-1371    [000] D..2.   521.406664: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 3795993
>>>   cpumap/0/map:4-1371    [000] D..2.   522.407469: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 3949519
>>>   cpumap/0/map:4-1371    [000] D..2.   523.408126: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 4365335
>>>   cpumap/0/map:4-1371    [000] D..2.   524.408929: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 4154910
>>>   cpumap/0/map:4-1371    [000] D..2.   525.410048: bpf_trace_printk:
>>> (tc) Send performance event (5,1), 4405582
>>>   cpumap/0/map:4-1371    [000] D..2.   525.434080: bpf_trace_printk:
>>> (tc) Send flow event
>>>   cpumap/0/map:4-1371    [000] D..2.   525.482714: bpf_trace_printk:
>>> (tc) Send flow event
>>>
>>> The times haven't been tweaked yet. The (5,1) is tc handle major/minor,
>>> allocated by the xdp-cpumap parent.
>>> I get pretty low latency between VMs; I'll set up a test with some
>>> real-world data very soon.
>>>
>>> I plan to keep hacking away, but feel free to take a peek.
>>>
>>> Thanks,
>>> Herbert
>>>
>>> On Mon, Oct 17, 2022 at 10:14 AM Simon Sundberg <Simon.Sundberg at kau.se>
>>> wrote:
>>>
>>>> Hi, thanks for adding me to the conversation. Just a couple of quick
>>>> notes.
>>>>
>>>> On Mon, 2022-10-17 at 16:13 +0200, Toke Høiland-Jørgensen wrote:
>>>> > [ Adding Simon to Cc ]
>>>> >
>>>> > Herbert Wolverson via LibreQoS <libreqos at lists.bufferbloat.net>
>>>> writes:
>>>> >
>>>> > > Hey,
>>>> > >
>>>> > > I've had some pretty good success with merging xdp-pping (
>>>> > >
>>>> https://github.com/xdp-project/bpf-examples/blob/master/pping/pping.h )
>>>> > > into xdp-cpumap-tc ( https://github.com/xdp-project/xdp-cpumap-tc
>>>> ).
>>>> > >
>>>> > > I ported over most of the xdp-pping code, and then changed the
>>>> entry point
>>>> > > and packet parsing code to make use of the work already done in
>>>> > > xdp-cpumap-tc (it's already parsed a big chunk of the packet, no
>>>> need to do
>>>> > > it twice). Then I switched the maps to per-cpu maps, and had to pin
>>>> them -
>>>> > > otherwise the two tc instances don't properly share data.
>>>> > >
>>>>
>>>> I guess the xdp-cpumap-tc ensures that the same flow is processed on
>>>> the same CPU core at both ingress or egress. Otherwise, if a flow may
>>>> be processed by different cores on ingress and egress the per-CPU maps
>>>> will not really work reliably as each core will have a different view
>>>> on the state of the flow, if there's been a previous packet with a
>>>> certain TSval from that flow etc.
>>>>
>>>> Furthermore, if a flow is always processed on the same core (on both
>>>> ingress and egress) I think per-CPU maps may be a bit wasteful on
>>>> memory. From my understanding the keys for per-CPU maps are still
>>>> shared across all CPUs, it's just that each CPU gets its own value. So
>>>> all CPUs will then have their own data for each flow, but it's only the
>>>> CPU processing the flow that will have any relevant data for the flow
>>>> while the remaining CPUs will just have an empty state for that flow.
>>>> Under the same assumption that packets within the same flow are always
>>>> processed on the same core there should generally not be any
>>>> concurrency issues with having a global (non-per-CPU) either as packets
>>>> from the same flow cannot be processed concurrently then (and thus no
>>>> concurrent access to the same value in the map). I am however still
>>>> very unclear on if there's any considerable performance impact between
>>>> global and per-CPU map versions if the same key is not accessed
>>>> concurrently.
>>>>
>>>> > > Right now, output
>>>> > > is just stubbed - I've still got to port the perfmap output code.
>>>> Instead,
>>>> > > I'm dumping a bunch of extra data to the kernel debug pipe, so I
>>>> can see
>>>> > > roughly what the output would look like.
>>>> > >
>>>> > > With debug enabled and just logging I'm now getting about 4.9
>>>> Gbits/sec on
>>>> > > single-stream iperf between two VMs (with a shaper VM in the
>>>> middle). :-)
>>>> >
>>>> > Just FYI, that "just logging" is probably the biggest source of
>>>> > overhead, then. What Simon found was that sending the data from kernel
>>>> > to userspace is one of the most expensive bits of epping, at least
>>>> when
>>>> > the number of data points goes up (which is does as additional flows
>>>> are
>>>> > added).
>>>>
>>>> Yhea, reporting individual RTTs when there's lots of them (you may get
>>>> upwards of 1000 RTTs/s per flow) is not only problematic in terms of
>>>> direct overhead from the tool itself, but also becomes demanding for
>>>> whatever you use all those RTT samples for (i.e. need to log, parse,
>>>> analyze etc. a very large amount of RTTs). One way to deal with that is
>>>> of course to just apply some sort of sampling (the -r/--rate-limit and
>>>> -R/--rtt-rate
>>>> >
>>>> > > So my question: how would you prefer to receive this data? I'll
>>>> have to
>>>> > > write a daemon that provides userspace control (periodic cleanup as
>>>> well as
>>>> > > reading the performance stream), so the world's kinda our oyster. I
>>>> can
>>>> > > stick to Kathie's original format (and dump it to a named pipe,
>>>> perhaps?),
>>>> > > a condensed format that only shows what you want to use, an
>>>> efficient
>>>> > > binary format if you feel like parsing that...
>>>> >
>>>> > It would be great if we could combine efforts a bit here so we don't
>>>> > fork the codebase more than we have to. I.e., if "upstream" epping and
>>>> > whatever daemon you end up writing can agree on data format etc that
>>>> > would be fantastic! Added Simon to Cc to facilitate this :)
>>>> >
>>>> > Briefly what I've discussed before with Simon was to have the ability
>>>> to
>>>> > aggregate the metrics in the kernel (WiP PR [0]) and have a userspace
>>>> > utility periodically pull them out. What we discussed was doing this
>>>> > using an LPM map (which is not in that PR yet). The idea would be that
>>>> > userspace would populate the LPM map with the keys (prefixes) they
>>>> > wanted statistics for (in LibreQOS context that could be one key per
>>>> > customer, for instance). Epping would then do a map lookup into the
>>>> LPM,
>>>> > and if it gets a match it would update the statistics in that map
>>>> entry
>>>> > (keeping a histogram of latency values seen, basically). Simon's PR
>>>> > below uses this technique where userspace will "reset" the histogram
>>>> > every time it loads it by swapping out two different map entries when
>>>> it
>>>> > does a read; this allows you to control the sampling rate from
>>>> > userspace, and you'll just get the data since the last time you
>>>> polled.
>>>>
>>>> Thank's Toke for summarzing both the current state and the plan going
>>>> forward. I will just note that this PR (and all my other work with
>>>> ePPing/BPF-PPing/XDP-PPing/I-suck-at-names-PPing) will be more or less
>>>> on hold for a couple of weeks right now as I'm trying to finish up a
>>>> paper.
>>>>
>>>> > I was thinking that if we all can agree on the map format, then your
>>>> > polling daemon could be one userspace "client" for that, and the
>>>> epping
>>>> > binary itself could be another; but we could keep compatibility
>>>> between
>>>> > the two, so we don't duplicate effort.
>>>> >
>>>> > Similarly, refactoring of the epping code itself so it can be plugged
>>>> > into the cpumap-tc code would be a good goal...
>>>>
>>>> Should probably do that...at some point. In general I think it's a bit
>>>> of an interesting problem to think about how to chain multiple XDP/tc
>>>> programs together in an efficent way. Most XDP and tc programs will do
>>>> some amount of packet parsing and when you have many chained programs
>>>> parsing the same packets this obviously becomes a bit wasteful. In the
>>>> same time it would be nice if one didn't need to manually merge
>>>> multiple programs together into a single one like this to get rid of
>>>> this duplicated parsing, or at least make that process of merging those
>>>> programs as simple as possible.
>>>>
>>>>
>>>> > -Toke
>>>> >
>>>> > [0] https://github.com/xdp-project/bpf-examples/pull/59
>>>>
>>>> När du skickar e-post till Karlstads universitet behandlar vi dina
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>>>> When you send an e-mail to Karlstad University, we will process your
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>>>>
>>> _______________________________________________
>>> LibreQoS mailing list
>>> LibreQoS at lists.bufferbloat.net
>>> https://lists.bufferbloat.net/listinfo/libreqos
>>>
>>
>>
>> --
>> Robert Chacón
>> CEO | JackRabbit Wireless LLC <http://jackrabbitwireless.com>
>>
>
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