[yocto] Suitable machine for yocto

[Alex Lennon]

On 10/09/2017 19:17, Mark Hatle wrote:
> On 9/10/17 11:14 AM, Alex Lennon wrote:
>>
>> On 10/09/2017 17:06, Mark Hatle wrote:
>>> On 9/10/17 2:00 AM, Usman Haider wrote:
>>>> Hi,
>>>>
>>>> Can someone please recommend some good machine for yocto environment and
>>>> building sdks. I am interested in RAM, hard disk space, processor.
>>> You want fast I/O, as much RAM and as many (fast) cores as you can afford.  I
>>> don't think there is a single answer as what is 'best'.  It also depends on
>>> which Yocto Project versions, and which layers you are using as to which
>>> combination is best.
>>>
>>> I run builds on my laptop, 4-core/8-thread & SSD and 16 GB of ram from a few
>>> years ago.  It's fast, but I wouldn't want to do all of my development on it.
>>>
>>> I've had 8-core/16-thread (32GB ram/standard disk), 16-core/32-thread (72GB
>>> ram/SAS-3 RAID), 24-core/48-thread (64GB ram/SATA - software RAID), 72-core/144
>>> thread (256 GB ram/hardware raid/SAS-3), and recently upgraded to
>>> 96-core/192-thread (256 GB ram/hardware raid/SAS-3).
>>>
>>> I would not go below quad-core (8-thread) myself.  You can get a quad core, good
>>> quality machine for $1000 or less these day.  If you move up to the larger
>>> machines, you can even be able to get to a 24-core for less then $5000.  By the
>>> time you get to 96-core and all of the googles you are likely talking $50000 or
>>> more.
>>>
>>> By clock raid, the 24-core machine is the fastest..  While the 96-core monster
>>> can do the builds the quickest.  But when you figure out cost/performance/etc..
>>> the 24-core is probably the best performance per dollar, and with adequate RAM
>>> (I'd say at least 64GB if not 128GB), and fast I/O you'll probably get the
>>> lowest price for the best performance in that category.
>>>
>>> If you need sheer speed and price is no option, then the (4 CPU w/ 24 core each)
>>> 96-core monster (or even better) is what you want to go with.  256GB ram would
>>> be a minimum with that configuration (I'm not sure if more is actually helpful,
>>> I rarely end up in swap -- but I go get into situations where more then 50% of
>>> ram is used.)  With that many cores, disk I/O starts to become obvious.  So
>>> faster the better... SSDs would be the fastest, but of course the most expensive.
>>>
>>> If your employer is paying for the machine, you may be able to get a better then
>>> normal machine by explaining how much time a faster machine will save and how
>>> comparing to your salary a machine is inexpensive.  (If you are a contractor or
>>> student, that changes of course.)  :)
>>>
>>> So my point is really, figure out how much money you have to spend.  My rule of
>>> thumb is roughly:
>>>
>>> 1) Buy as many cores as you can.  Try to get a CPU that has Hyperthreading or
>>> equivalent to double the effective core count.  Fastest processing speed helps
>>> in repetitive cases vs full system builds.
>>>
>>> So if the choice is a 24 core @ 2.2GHz vs 22 core @ 2.5, I'd probably go with
>>> the 22-core.  While if it was 24 core @ 2.2GHz vs 8 core @ 4.2 GHz, I'd go with
>>> the 24 core.
>>>
>>> 2) Try to get at least 1 GB of ram per thread (2 GB per core..)  You can cut
>>> back on the ram (if necessary) once you hit 72 threads or so.   (72 threads
>>> right now seems to cover most of the parallelization in a full system build.
>>> There are points in the system where it can parallelize MUCH more, but they are
>>> fairly rare.)
>>>
>>> 3) You need fast disks.  Software RAID works fine, but you likely need to buy at
>>> least a couple of disk to boost performance.  SSDs are fast, but lots of builds
>>> take space, so fast SATA or even better SAS drives are the best performance per
>>> cost.
>> This brings to mind a related question I keep coming back to as to the
>> economics of a docker (or similar) image running a fast Yocto build in
>> the cloud.
>>
>> i.e. set config params -> bring up server image on plaform A/B/C ->
>> perform build taking time X/Y/Z -> store output images -> bring down
>> server  == $ ?
>>
>> I find myself asking what the optimal cost per-build would be using this
>> approach...
> I helped someone do some very -preliminary- figured a few years ago.  The
> processing was 'cheap', but between storage and network transfer costs.. it was
> cheaper to buy a reasonable machine.. payback time was only a few months.
>
> (cloud 'storage' is often very slow as well, because there are expectations of
> migration and things like that.)
>
> So as of a few years ago at least, the economics didn't factory the cloud -- yet.
>
>

Yeah that is more or less my thinking. Although I do imagine that if a 
source mirror on an internal network leg could be set up then that might 
significantly reduce chargeable network b/w...

Cheers,

Alex