From: Axel Kohlmeyer (akohlmey_at_gmail.com)
Date: Mon May 28 2012 - 17:19:42 CDT
On Mon, May 28, 2012 at 6:11 PM, Francesco Pietra <chiendarret_at_gmail.com> wrote:
> As to "CPU memory bandwidth" "PCI bandwidth", it would be useful to
> have tabulated data in physically unambiguous terms (bit/s or what
> else) for typical motherboards and CPU GPU mem. It would provide a
> ground of reference on which to pose questions to hardware producers
> about their hardware. At least with consumer motherboards (but also
> with certain server motherboards, such as the one I have from
> Supermicro), indications are never numeric and often even the word
> bandwidth is omitted.
are you going to volunteer to generate, collect and maintain this data?
> francesco pietra
> On Mon, May 28, 2012 at 9:58 PM, Axel Kohlmeyer <akohlmey_at_gmail.com> wrote:
>> On Sun, May 27, 2012 at 10:10 AM, Benjamin Merget
>> <benjamin.merget_at_uni-wuerzburg.de> wrote:
>>> The problem is, that I can only reach up to about 25% gpu utilization of
>>> each of the 4 Tesla cards. I thought that maybe I could increase the GPU
>>> utilization by creating more processes to bind to the Tesla cards. But to do
>>> so, I need more CPUs, i.e. the CPUs of my CPU-only nodes...
>> no. that won't work. if you have a low GPU utilization
>> then this is more likely due to:
>> - your simulation system is too small to result in good
>> GPU utilization. remember that you need to have sufficient
>> GPU work to offset the cost or data transfers to and from
>> the GPU and also the non-accelerated work on the CPU.
>> attaching more processes to one GPU reduces the latter,
>> but increases the number of (competing) data transfers.
>> - your host machine's CPU doesn't have much memory bandwidth
>> - your GPUs are not in full bandwidth PCIe v2.x slots,
>> or you have a PCIe v1.x card somewhere that reduces
>> the neighboring GPU to drop to PCIe v1.x speed as well.
>> (depends on the main board)
>>> Is there another way to increase my GPU utilization with the 8 CPU cores of
>>> my GPU node?
>> maybe. but that depends on the cause and that is
>> impossible to tell from remote.
>>>> no, and it is not worth it. just run one calculation on the GPU node
>>>> and a second on the rest and enjoy efficient utilization of your hardware.
>>>> anything else is just wasting your time.
>> Dr. Axel Kohlmeyer
>> College of Science and Technology
>> Temple University, Philadelphia PA, USA.
-- Dr. Axel Kohlmeyer akohlmey_at_gmail.com http://goo.gl/1wk0 College of Science and Technology Temple University, Philadelphia PA, USA.
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