Re: [AMBER] How many GPU card is working

From: Saikat Pal <saikatpaliitg.yahoo.com>
Date: Fri, 18 Aug 2017 13:50:13 +0000 (UTC)

Thank you Sir for your kind response. If I will run amber in single gpu how many cpu per task should I take for best run (means less time consuming)??I have 24 cpus.
 Thanks and Regards,Saikat


On Friday 18 August 2017, 6:39:42 PM IST, Daniel Roe <daniel.r.roe.gmail.com> wrote:

Your motherboard needs to support it and the GPUs need to be arranged
so that they are on the same PCI bus. See this post for a good
description of P2P:

http://exxactcorp.com/blog/exploring-the-complexities-of-pcie-connectivity-and-peer-to-peer-communication/

-Dan

On Fri, Aug 18, 2017 at 8:35 AM, Saikat Pal <saikatpaliitg.yahoo.com> wrote:
> Thank you Sir for your kind response.In mdout file :--------------- GPU PEER TO PEER INFO -----------------
> |
> |  Peer to Peer support: DISABLED
> |
> |        (Selected GPUs cannot communicate over P2P)
> |
> |--------------------------------------------------------
>
>
> How can I enable Peer to Peer support??
> Thanks and Regards,Saikat
> On Friday 18 August 2017, 5:45:37 PM IST, Daniel Roe <daniel.r.roe.gmail.com> wrote:
>
> Hi,
>
> On Fri, Aug 18, 2017 at 7:33 AM, Saikat Pal <saikatpaliitg.yahoo.com> wrote:
>> Dear all,How many GPU card is working ??I think it is 10 but not sure.Please help me.Thanks Saikat
>
> It's 2. According to your output CUDA_VISIBLE_DEVICES is set to "0,1",
> and there are 2 CUDA capable devices detected. Right now 3 tasks are
> running on one GPU and 3 on the other, which is almost certainly not
> what you want. You may get some speedup running across 2 GPUs if
> peer-to-peer support is enabled, but you should benchmark. More useful
> info on running on multiple GPUs can be found here:
> http://ambermd.org/gpus/index.htm#Running
>
> -Dan
>
>>
>>
>> ------------------- GPU DEVICE INFO --------------------
>> |
>> |                        Task ID:      0
>> |            CUDA_VISIBLE_DEVICES: 0,1
>> |  CUDA Capable Devices Detected:      2
>> |          CUDA Device ID in use:      0
>> |                CUDA Device Name: Tesla K40c
>> |    CUDA Device Global Mem Size:  11519 MB
>> | CUDA Device Num Multiprocessors:    15
>> |          CUDA Device Core Freq:  0.75 GHz
>> |
>> |
>> |                        Task ID:      1
>> |            CUDA_VISIBLE_DEVICES: 0,1
>> |  CUDA Capable Devices Detected:      2
>> |          CUDA Device ID in use:      0
>> |                CUDA Device Name: Tesla K40c
>> |    CUDA Device Global Mem Size:  11519 MB
>> | CUDA Device Num Multiprocessors:    15
>> |          CUDA Device Core Freq:  0.75 GHz
>> |
>> |
>> |                        Task ID:      2
>> |            CUDA_VISIBLE_DEVICES: 0,1
>> |  CUDA Capable Devices Detected:      2
>> |          CUDA Device ID in use:      1
>> |                CUDA Device Name: Tesla K40c
>> |    CUDA Device Global Mem Size:  11519 MB
>> | CUDA Device Num Multiprocessors:    15
>> |          CUDA Device Core Freq:  0.75 GHz
>> |
>> |
>> |                        Task ID:      3
>> |            CUDA_VISIBLE_DEVICES: 0,1
>> |  CUDA Capable Devices Detected:      2
>> |          CUDA Device ID in use:      1
>> |                CUDA Device Name: Tesla K40c
>> |    CUDA Device Global Mem Size:  11519 MB
>> | CUDA Device Num Multiprocessors:    15
>> |          CUDA Device Core Freq:  0.75 GHz
>> |
>> |
>> |                        Task ID:      4
>> |            CUDA_VISIBLE_DEVICES: 0,1
>> |  CUDA Capable Devices Detected:      2
>> |          CUDA Device ID in use:      0
>> |                CUDA Device Name: Tesla K40c
>> |    CUDA Device Global Mem Size:  11519 MB
>> | CUDA Device Num Multiprocessors:    15
>> |          CUDA Device Core Freq:  0.75 GHz
>> |
>> |
>> |                        Task ID:      5
>> |            CUDA_VISIBLE_DEVICES: 0,1
>> |  CUDA Capable Devices Detected:      2
>> |          CUDA Device ID in use:      0
>> |                CUDA Device Name: Tesla K40c
>> |    CUDA Device Global Mem Size:  11519 MB
>> | CUDA Device Num Multiprocessors:    15
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>
>
>
> --
> -------------------------
> Daniel R. Roe
> Laboratory of Computational Biology
> National Institutes of Health, NHLBI
> 5635 Fishers Ln, Rm T900
> Rockville MD, 20852
> https://www.lobos.nih.gov/lcb
>
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-- 
-------------------------
Daniel R. Roe
Laboratory of Computational Biology
National Institutes of Health, NHLBI
5635 Fishers Ln, Rm T900
Rockville MD, 20852
https://www.lobos.nih.gov/lcb
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Received on Fri Aug 18 2017 - 07:00:04 PDT
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