[LibreQoS] In BPF pping - so far

[Robert Chacón]

Awesome work on this!
I suspect there should be a slight performance bump once Hyperthreading is
disabled and efficient power management is off.
Hyperthreading/SMT always messes with HTB performance when I leave it on.
Thank you for mentioning that - I now went ahead and added instructions on
disabling hyperthreading on the Wiki for new users.
Super promising results!
Interested to see what throughput is with xdp-cpumap-tc vs cpumap-pping. So
far in your VM setup it seems to be doing very well.

On Wed, Oct 19, 2022 at 8:06 AM Herbert Wolverson via LibreQoS <
libreqos at lists.bufferbloat.net> wrote:

> Also, I forgot to mention that I *think* the current version has removed
> the requirement that the inbound
> and outbound classifiers be placed on the same CPU. I know interduo was
> particularly keen on packing
> upload into fewer cores. I'll add that to my list of things to test.
>
> On Wed, Oct 19, 2022 at 9:01 AM Herbert Wolverson <herberticus at gmail.com>
> wrote:
>
>> I'll definitely take a look - that does look interesting. I don't have
>> X11 on any of my test VMs, but
>> it looks like it can work without the GUI.
>>
>> Thanks!
>>
>> On Wed, Oct 19, 2022 at 8:58 AM Dave Taht <dave.taht at gmail.com> wrote:
>>
>>> could I coax you to adopt flent?
>>>
>>> apt-get install flent netperf irtt fping
>>>
>>> You sometimes have to compile netperf yourself with --enable-demo on
>>> some systems.
>>> There are a bunch of python libs neede for the gui, but only on the
>>> client.
>>>
>>> Then you can run a really gnarly test series and plot the results over
>>> time.
>>>
>>> flent --socket-stats --step-size=.05 -t 'the-test-conditions' -H
>>> the_server_name rrul # 110 other tests
>>>
>>>
>>> On Wed, Oct 19, 2022 at 6:44 AM Herbert Wolverson via LibreQoS
>>> <libreqos at lists.bufferbloat.net> wrote:
>>> >
>>> > 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
>>> personuppgifter<https://www.kau.se/gdpr>.
>>> >>>>> When you send an e-mail to Karlstad University, we will process
>>> your personal data<https://www.kau.se/en/gdpr>.
>>> >>>>
>>> >>>> _______________________________________________
>>> >>>> LibreQoS mailing list
>>> >>>> LibreQoS at lists.bufferbloat.net
>>> >>>> https://lists.bufferbloat.net/listinfo/libreqos
>>> >>>
>>> >>>
>>> >>>
>>> >>> --
>>> >>> Robert Chacón
>>> >>> CEO | JackRabbit Wireless LLC
>>> >
>>> > _______________________________________________
>>> > LibreQoS mailing list
>>> > LibreQoS at lists.bufferbloat.net
>>> > https://lists.bufferbloat.net/listinfo/libreqos
>>>
>>>
>>>
>>> --
>>> This song goes out to all the folk that thought Stadia would work:
>>>
>>> https://www.linkedin.com/posts/dtaht_the-mushroom-song-activity-6981366665607352320-FXtz
>>> Dave Täht CEO, TekLibre, LLC
>>>
>> _______________________________________________
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-- 
Robert Chacón
CEO | JackRabbit Wireless LLC <http://jackrabbitwireless.com>
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