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Date:	Sat, 16 Apr 2016 11:52:05 +0300
From:	Andrew <nitr0@...i.kr.ua>
To:	Michael Ma <make0818@...il.com>,
	Jesper Dangaard Brouer <brouer@...hat.com>
Cc:	netdev@...r.kernel.org
Subject: Re: qdisc spin lock

I think that it isn't a good solution - unless you can bind specified 
host (src/dst) to specified txq. Usually traffic is spreaded on txqs by 
src+dst IP (or even IP:port) hash which results in traffic spreading 
among all mqs on device, and wrong bandwidth limiting (N*bandwidth on 
multi-session load like p2p/server traffic)...

People said that hfsc shaper have better performance, but I didn't 
tested it.

01.04.2016 02:41, Michael Ma пишет:
> Thanks for the suggestion - I'll try the MQ solution out. It seems to
> be able to solve the problem well with the assumption that bandwidth
> can be statically partitioned.
>
> 2016-03-31 12:18 GMT-07:00 Jesper Dangaard Brouer <brouer@...hat.com>:
>> On Wed, 30 Mar 2016 00:20:03 -0700 Michael Ma <make0818@...il.com> wrote:
>>
>>> I know this might be an old topic so bare with me – what we are facing
>>> is that applications are sending small packets using hundreds of
>>> threads so the contention on spin lock in __dev_xmit_skb increases the
>>> latency of dev_queue_xmit significantly. We’re building a network QoS
>>> solution to avoid interference of different applications using HTB.
>> Yes, as you have noticed with HTB there is a single qdisc lock, and
>> congestion obviously happens :-)
>>
>> It is possible with different tricks to make it scale.  I believe
>> Google is using a variant of HTB, and it scales for them.  They have
>> not open source their modifications to HTB (which likely also involves
>> a great deal of setup tricks).
>>
>> If your purpose it to limit traffic/bandwidth per "cloud" instance,
>> then you can just use another TC setup structure.  Like using MQ and
>> assigning a HTB per MQ queue (where the MQ queues are bound to each
>> CPU/HW queue)... But you have to figure out this setup yourself...
>>
>>
>>> But in this case when some applications send massive small packets in
>>> parallel, the application to be protected will get its throughput
>>> affected (because it’s doing synchronous network communication using
>>> multiple threads and throughput is sensitive to the increased latency)
>>>
>>> Here is the profiling from perf:
>>>
>>> -  67.57%   iperf  [kernel.kallsyms]     [k] _spin_lock
>>>    - 99.94% dev_queue_xmit
>>>    -  96.91% _spin_lock
>>>   - 2.62%  __qdisc_run
>>>    - 98.98% sch_direct_xmit
>>> - 99.98% _spin_lock
>>>
>>> As far as I understand the design of TC is to simplify locking schema
>>> and minimize the work in __qdisc_run so that throughput won’t be
>>> affected, especially with large packets. However if the scenario is
>>> that multiple classes in the queueing discipline only have the shaping
>>> limit, there isn’t really a necessary correlation between different
>>> classes. The only synchronization point should be when the packet is
>>> dequeued from the qdisc queue and enqueued to the transmit queue of
>>> the device. My question is – is it worth investing on avoiding the
>>> locking contention by partitioning the queue/lock so that this
>>> scenario is addressed with relatively smaller latency?
>> Yes, there is a lot go gain, but it is not easy ;-)
>>
>>> I must have oversimplified a lot of details since I’m not familiar
>>> with the TC implementation at this point – just want to get your input
>>> in terms of whether this is a worthwhile effort or there is something
>>> fundamental that I’m not aware of. If this is just a matter of quite
>>> some additional work, would also appreciate helping to outline the
>>> required work here.
>>>
>>> Also would appreciate if there is any information about the latest
>>> status of this work http://www.ijcset.com/docs/IJCSET13-04-04-113.pdf
>> This article seems to be very low quality... spelling errors, only 5
>> pages, no real code, etc.
>>
>> --
>> Best regards,
>>    Jesper Dangaard Brouer
>>    MSc.CS, Principal Kernel Engineer at Red Hat
>>    Author of http://www.iptv-analyzer.org
>>    LinkedIn: http://www.linkedin.com/in/brouer

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