[concurrency-interest] Benchmark to demonstrate improvement in thread management over the years.

Jason Koch jasonk at bluedevel.com
Mon Aug 12 18:16:14 EDT 2013

Theoretically - they should both have similar behaviours in theory, and the
issue is the implementation. This is a very good background paper on the
topic - http://www.stanford.edu/class/cs240/readings/vonbehren.pdf - and is
well worth reading. In my interpretation, they present threads/events as
duals of each other.

There is no reason we can't have lighter threading models. Erlang/BEAM is
known to scale to extremely high concurrent process counts with ease, and
Kilim on the JVM looks like a promising way to get lightweight threading
(though I'm yet to try it unfortunately). Similarly, you can write a slow
evented implementation if you choose to.

In practice, OS threading tends to have a heavy footprint and challenges
context switching, where events can have a very controlled footprint. For
example, a full thread stack is usually a few hundred KB, where an event
state machine can often be modeled in a handful of bytes up to a few KB.

So, in practice on Linux, with C or Java or on the MS/.net platform, events
and async IO tend to be much more scalable. There are tradeoffs you need to
make in your design, but these tradeoffs for certain types of applications
are very worthwhile - eg: web servers.


On Tue, Aug 13, 2013 at 1:06 AM, Vitaly Davidovich <vitalyd at gmail.com>wrote:

> Yes, that's a good point.  I think LinkedIn had a presentation on their
> use of Play, and touched upon this exact scenario (web server having to
> aggregate/join data from different backend systems).  The other problem
> with calling out to backend servers using a threaded model (besides memory
> charge) is that slowness in just one or two of them can ripple throughout
> entire infrastructure, possibly leading to entire site being down.
> Sent from my phone
> On Aug 12, 2013 10:27 AM, "James Roper" <james.roper at typesafe.com> wrote:
>> It's also worth pointing out that the thread per request model is
>> becoming less feasible even for simple web apps. Modern service oriented
>> architectures often require that a single web request may make many
>> requests to other backend services. At the extreme, we see users writing
>> Play apps that make hundreds of backend API calls per request. In order to
>> provide acceptable response times, these requests must be made in parallel.
>> With blocking IO, that would mean a single request might take 100 threads,
>> if you had just 100 concurrent requests, that's 10000 threads, if each
>> thread stack takes 100kb of real memory, that's 1GB memory just for thread
>> stacks. That's not cheap.
>> Regards,
>> James
>> On Aug 13, 2013 12:08 AM, "Vitaly Davidovich" <vitalyd at gmail.com> wrote:
>>> I don't have any benchmarks to give, but I don't think the touted
>>> benefits of an evented model includes CPU performance.  Rather, using an
>>> evented model allows you to scale.  Specific to a web server, you want to
>>> be able to handle lots of concurrent connections (most of them are probably
>>> idle at any given time) while minimizing resource usage to accomplish that.
>>> With a thread-per-request (threaded) model, you may end up using lots of
>>> threads but most of them are blocked on i/o at any given time.  A slow
>>> client/consumer can tie up a thread for a very long time.  This also makes
>>> the server susceptible to a DDoS attack whereby new connections are
>>> established, but the clients are purposely slow to tie up the server
>>> threads.  Resource usage is also much higher in the threaded model when you
>>> have tens of thousands of connections since you're going to pay for stack
>>> space for each thread (granted it's VM space, but still).
>>> With an evented model, you don't have the inefficiency of having
>>> thousands of threads alive but that are blocked/waiting on i/o.  A single
>>> thread dedicated to multiplexing i/o across all the connections will
>>> probably be sufficient.  The rest is worker threads (most likely = # of
>>> CPUs for a dedicated machine) that actually handle the request processing,
>>> but don't do any (significant) i/o.  This design also means that you can
>>> handle slow clients in a more robust manner.
>>> So, the cost of threads can be "heavy" in the case of very busy web
>>> servers.  The Linux kernel should handle a few thousand threads (most
>>> blocked on io) quite well, but I don't think that will be the case for tens
>>> or hundreds of thousands.  Even if there's sufficient RAM to handle that
>>> many, there may be performance issues coming from the kernel itself, e.g.
>>> scheduler.  At the very least, you'll be using resources of the machine
>>> inefficiently under that setup.
>>> Vitaly
>>> Sent from my phone
>>> On Aug 12, 2013 9:13 AM, "Unmesh Joshi" <unmeshjoshi at gmail.com> wrote:
>>>> Hi,
>>>> Most of the books on node.js, Akka, Play or any other event IO based
>>>> system frequently talk about 'Threads' being heavy and there is cost we
>>>> have to pay for all the booking the OS or the JVM has to do with all the
>>>> threads.
>>>> While I agree that there must be some cost and for doing CPU intensive
>>>> tasks like matrix multiplication, and fork-join kind of framework will be
>>>> more performant, I am not sure if for web server kind of IO intensive
>>>> application that's the case.
>>>> On the contrary, I am seeing web servers running on tomcat with 1000 +
>>>> threads without issues.  For web servers. I think that Linux level thread
>>>> management has improved a lot in last 10 years. Same is with the JVM.
>>>> Do we have any benchmark which shows how much Linux thread management
>>>> and JVM thread management have improved over the years?
>>>> Thanks,
>>>> Unmesh
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