Hi Ciro,

I debugged my program and found that it got stuck at 'for i,data in 
enumerate(dataloader)'. I did some research 
https://discuss.pytorch.org/t/dataloader-iteration-hang-up/12886. It said that 
the argument of Dataloader object --num_workers > 0 would specify how many 
python subprocesses to use for data loading. Meanwhile, I checked the back 
stack at which my program got stuck and it showed the multiprocessing package 
of python. I have tried many ways to ban the multiprocessing of python 
including set num_workers = 0 but it did not work. BTW, my program could work 
normally if I mount my disk image and chroot. I am really confused. Is it due 
to gem5 lack of enough support for OS? And I also don't know why I cannot ban 
the multiprocessing of python. Any advice would be highly appreciated.

Best regards,

Yifan Song

> -----原始邮件-----
> 发件人: "syf1997--- via gem5-users" <gem5-users@gem5.org>
> 发送时间: 2020-08-09 14:50:29 (星期日)
> 收件人: "gem5 users mailing list" <gem5-users@gem5.org>
> 抄送: syf1...@mail.ustc.edu.cn
> 主题: [gem5-users] Re: gem5 aborted when increase mem-size in FS mode
> 
> 
> A few seconds after I login using m5term. But when I changed a new kernel 
> vmlinux-5.2.4 it could work except got stuck at training section. I checked 
> it out by mounting the disk image on my own machine and I saw the warning 
> :cannot found /proc/cpuinfo. I think it is beacause I use AomaticCPU. But 
> when I used TimingSimpleCPU and /proc/cpuinfo did exit, my program still got 
> stuck. Could you give some suggestions? Thank you
> 
> Best regards,
> 
> Yifan Song
> 
> > -----原始邮件-----
> > 发件人: "Ciro Santilli via gem5-users" <gem5-users@gem5.org>
> > 发送时间: 2020-08-06 15:11:57 (星期四)
> > 收件人: "gem5 users mailing list" <gem5-users@gem5.org>
> > 抄送: syf1...@mail.ustc.edu.cn, "Ciro Santilli" <ciro.santi...@gmail.com>
> > 主题: [gem5-users] Re: gem5 aborted when increase mem-size in FS mode
> > 
> > Does it crash immediately? If so, provide to us and look at the
> > backtrace to try and determine which allocation fails. If that doesn't
> > help, you can also try techniques mentioned at:
> > https://stackoverflow.com/questions/6261201/how-to-find-memory-leak-in-a-c-code-project/57877190#57877190
> > 
> > On Thu, Aug 6, 2020 at 2:44 AM syf1997--- via gem5-users
> > <gem5-users@gem5.org> wrote:
> > >
> > > Hi Jason,
> > >
> > > Thank you for your reply. I am using the latest version 20.3. I have just 
> > > double-checked the memory usage info of gem5. It showed that memory usage 
> > > is about 10GB, while I run gem5 on a 128GB memory server. I don't think 
> > > my system ran out of memory. I am confused about it.
> > >
> > > Yifan Song
> > >
> > > -----原始邮件-----
> > > 发件人:"Jason Lowe-Power via gem5-users" <gem5-users@gem5.org>
> > > 发送时间:2020-08-06 01:13:59 (星期四)
> > > 收件人: "gem5 users mailing list" <gem5-users@gem5.org>
> > > 抄送: syf1...@mail.ustc.edu.cn, "Jason Lowe-Power" <ja...@lowepower.com>
> > > 主题: [gem5-users] Re: gem5 aborted when increase mem-size in FS mode
> > >
> > > Hi Yifan,
> > >
> > > Is it possible that your system is running out of memory? It's possible 
> > > this is a gem5 bug (what version are you using?), but I haven't heard of 
> > > this issue before.
> > >
> > > Cheers,
> > > Jason
> > >
> > > On Wed, Aug 5, 2020 at 1:34 AM syf1997--- via gem5-users 
> > > <gem5-users@gem5.org> wrote:
> > >>
> > >> Hi all,
> > >>
> > >> I am trying to run my own program (training a tiny vgg16 CNN model using 
> > >> CPU) in FS mode. I have created my own disk image and installed python3 
> > >> and pytorch on it. My command line is as bellow:
> > >>
> > >> build/X86/gem5.opt configs/example/fs.py --kernel=binary/vmlinux-5.2.4 
> > >> --disk-image=disk/linux-x86.img -n 2 --caches --l2cache --mem-size=4GB
> > >>
> > >> If I set the mem-size small, like 512MB, 1GB, 2GB, my program could run 
> > >> normally but would fail due to the small memory. On the other hand, if I 
> > >> increase the mem-size, my program could not run and gem5 aborted (core 
> > >> dump). Could anyone give me some advice? Thanks.
> > >>
> > >> Best regards,
> > >>
> > >> Yifan
> > >>
> > >> _______________________________________________
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