Minimum hardware specs

[ButlerRobotics]

This is more of a question than an issue but not sure of the appropriate place to ask.

I was wondering if you had a minimum hardware requirement for SegNet. I was hoping to run (not train) on a Jetson TX1.

Also I was wondering if this would train on a laptop. It's reasonably high spec for a laptop but I realise that we are talking ANNs here.

I was going to build but then I saw issue #21 (Out of memory error!!)

My laptop has a GTX970M: http://www.geforce.com/hardware/notebook-gpus/geforce-gtx-970m/specifications Here is more info on the TX1: http://www.nvidia.com/object/jetson-tx1-module.html

BTW I would like to congratulate you on the great work. The demo is impressive.

Cheers.

[ButlerRobotics]

Just tried it on my laptop (Nvidia GTX970M 4GB) and had the exact same result as issue #21, I am unable to train. This issue was never resolved so I am not sure how to move forward.

Is 4GB really not enough or is something else causing the problem?

[alexgkendall]

Thanks! I've been able to run SegNet on my laptop (GTX960M, 4gb) and a Jetson TK1 and Jetson TX1. As some advice, to reduce memory you can play with things like: input resolution, batch size, network width and depth.

[ButlerRobotics]

That is promising! I was hoping to deploy on the TX1.

Would you happen to have the prototext files for training on the 960M or did you only deploy to the laptop? I have tried reducing the images to half their resolution and batch size is only 1 but I am still having memory issues. Exactly the same as issue #21

Also I was wondering what kind of performance you got on the TX1. How much lag is there with live video?

[Timo-hab]

I was able to train it on a GTX980, 4GB. However, I had to change the batch size to 2. Unfortunately the results are not really well.

[Timo-hab]

I must correct myself. The results are after 40,000 iterations quite well. Before that I only tested with 10,000 iterations.

[ButlerRobotics]

Thanks for sharing. Good to know that 4GB can train with good results. Could you tell me what modifications you made in order to train on 4GB? I have not had any success with this. Was changing the batch size the only thing you changed!? I have tried with a batch size of 1 and still ran out of memory. Perhaps something wrong with my environment...

[Timo-hab]

I am surprising, that some have problems with 4 GB. I have only changed the batch size. Somewhere I read that cudnn version 2 is required. Actually I use version 3 (ver. 3.0.07, CUDA ver. 7.5). I could imagine that this is the reason.

[g41903]

I'm also encounter memory problem. I followed Segnet tutorial (https://githucom/alexgkendall/SegNet-Tutorial) on Jetson TX1 and ran webcam_demo.py. It crashes when it tried to do forward propagation of the network out = net.forward_all(data=input_image) and the error is

I0611 11:46:34.369215 19670 net.cpp:247] Network initialization done. I0611 11:46:34.369243 19670 net.cpp:248] Memory required for data: 1065139200 Here is videos Grabbed camera frame in 7.64513015747 ms Resized image in 126.845121384 ms Killed

I cleaned the cache and ran webcam_demo.py, but it doesn't work. Is there any suggestion?

My memory status is total used free shared buffers cached Mem: 3853 1735 2118 40 24 282 -/+ buffers/cache: 1428 2425 Swap: 0 0 0

[ButlerRobotics]

Thanks again Timo-hab. I had been told that I needed CUDA v2 for gpu acceleration but wasn't certain if this would fix the memory issue. Seems that this is the case then. Will try the old version...

[jeanpat]

Does it worth to fight to install segnet on a laptop with a nvidia gt740M ? I plan to train on greyscaled images not larger than 200x200.

~/App/samples/bin/x86_64/linux/release$ nvidia-smi 
Mon Jul 18 16:21:43 2016       
+------------------------------------------------------+                       
| NVIDIA-SMI 352.63     Driver Version: 352.63         |                       
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GT 740M     Off  | 0000:01:00.0     N/A |                  N/A |
| N/A   53C    P0    N/A /  N/A |      5MiB /  2047MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|    0                  Not Supported                                         |
+-----------------------------------------------------------------------------+

[JasonYLin]

I also have memory problem on Jetson TX1.

here is the error message:

I0324 14:17:41.216102 28333 net.cpp:247] Network initialization done. I0324 14:17:41.216142 28333 net.cpp:248] Memory required for data: 1065139200 Grabbed camera frame in 2.96902656555 ms Resized image in 7.36689567566 ms Killed

anyone has idea to solve it? Thanks!