[QUOTE=James Heinrich;535038]If Colab is truly "over", can someone volunteer to clean up the half-done exponents? I apparently have one at 91.6%, if Chris can send the checkpoint to whoever wants to finish it for me (I care nothing for credit).[/QUOTE]

I still have a single, old 560 online which I use for (slow) cleanup work. Unless anyone cares enough to ask me for the checkpoint files, I'll clear them out over the next few days. I should be able to bring a 1060 back online as well.

Just out of interest, today with an account that hasn't had a GPU backend for the last four days, I ran an experiment and Colab /did/ give me a CPU backend no problem, so we could still use Colab for some (slowish) CPU based work.

Secondly, does anyone out there have a Google account which they haven't used for the GPU72_TF Notebook in the past? An interesting experiment to run would be to see if a "virgin" account could get access, and if so, how long it lasted.

Because of the risk of being banned, I'd suggest one only do this with a "disposable" account.

[QUOTE=chalsall;535039]Secondly, does anyone out there have a Google account which they haven't used for the GPU72_TF Notebook in the past? An interesting experiment to run would be to see if a "virgin" account could get access, and if so, how long it lasted.[/QUOTE]I was able to get connected to a GPU on a previously-unused account. I didn't actually try running any work, but it does look like it's account specific.

[QUOTE=chalsall;535039]Secondly, does anyone out there have a Google account which they haven't used for the GPU72_TF Notebook in the past? An interesting experiment to run would be to see if a "virgin" account could get access, and if so, how long it lasted.

Because of the risk of being banned, I'd suggest one only do this with a "disposable" account.[/QUOTE]

I use CPUs on Colab almost every day. Just for the heck of it, I just now connected, asked for a GPU, and got one immediately. I didn't use it for anything, but I did get one.

[QUOTE=James Heinrich;535040]I didn't actually try running any work, but it does look like it's account specific.[/QUOTE]

Huh... Well I'll be...

Based on this, I just created another GMail account, using the same browser context as my three previous (now non-GPU) Colab accounts, used the same phone number of SMS confirmation, etc. Trying to be as honest as I could be.

Logged into Colab using the just created account, copy-and-pasted in the GPU72_TF Notebook, and launched it. Got a P100 first try!

I'll let you all know how long it survives. But this supports George's theory that there's a "life-time GPU quota", but apparently by account.

Perhaps Colab isn't actually dead yet. Finger's crossed...

Edit: 25 minutes... "She's dead, Jim."

The reports of Colab GIMPS use being dead are greatly exaggerated
 

[QUOTE=chalsall;535042]Perhaps Colab isn't actually dead yet. Finger's crossed...

Edit: 25 minutes... "She's dead, Jim."[/QUOTE]
The P100 I got for gpuowl continuation on Colab at 2020-01-13 15:51:41 UTC is still chugging along, at least to 2020-01-13 19:56:54. That's on the first Colab account, that I've been very frequently using. (Without chalsall's tunnels etc; straight colab from browser session, with google drive use.) The other one, also used daily or more when I can get a gpu, got a K80 and is still going at 7 hr 18 min uptime. Sometimes I get 10 hours, sometimes I don't. One went to 10:47 recently.
But then again, I think some of you got started a month before I did.
FYI, I have more than 25 Colab days (24-hour days, 600 hours) of gpu time logged in benchmarking gpuowl P-1 alone, on the first account.
P100 16.8
P4 1.0
K80 7.6

I keep using Colab on a daily basis (4 CPU instances) without any problem.
Two or three days ago I ran also two GPU mfaktc instances. May be because I had not use any GPU in a while (several weeks) I got two P100 straight away. But the fun only lasted for one hour or so. The accounts running only cpu instances were not affected. This is a pattern consistently observed lately: stick to cpus, and Colab will run like a charm; as soon as you touch a GPU, you're out.
So it seems that the availability of gpus is indeed a thing of the past, at least for most of us. I'll keep running mprime on 4 accounts. I have a few incomplete exponents from the gpu72 notebook that Chris may wish to finish off.

Dept of corrections
 

(Oops. Had P100 and K80 totals switched earlier)

P10010.1
P4 1.0
K80 16.8

Nearly all of that was joint cpu & gpu sessions. There were also some cpu-only mprime sessions not included in those subtotals when I could not get a gpu for a time.

Sometimes gpu-using sessions terminate early, sometimes not. Here's the last top -d 120 output before session end, from one that ran overnight, showing a run time of just over 10 hours:[CODE]Htop - 09:20:46 [B]up 10:02[/B], 0 users, load average: 1.05, 1.13, 1.10

%Cpu(s): 1.6 us, 1.7 sy, 49.9 ni, 46.8 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
KiB Mem : 13335180 total, 9070060 free, 1209308 used, 3055812 buff/cache
KiB Swap: 0 total, 0 free, 0 used. 12249416 avail Mem

373 root 30 10 555192 408036 8848 S 99.4 3.1 516:16.59 mprime
365 root 20 0 12.875g 191792 145276 S 1.7 1.4 9:43.65 [B]mfaktc[/B].e+
126 root 20 0 653984 152792 61752 S 0.5 1.1 3:05.81 python3
20 root 20 0 405212 101604 26672 S 0.1 0.8 0:50.33 jupyter-+
305 root 20 0 1388332 68636 25152 S 0.1 0.5 0:36.99 drive
10 root 20 0 690324 61476 24908 S 0.0 0.5 0:18.31 node
118 root 20 0 35888 4880 3784 S 0.0 0.0 0:01.52 tail
1 root 20 0 39192 6368 4864 S 0.0 0.0 0:00.03 run.sh [/CODE]
Some times of day seem better for getting a gpu than others.

Well, this is new
 

21+ hours and running on dual instance, cpu and K80 gpu, mprime and mfaktc, top -d 120 last output:[CODE]Htop - 14:11:57 [B]up 21:07[/B], 0 users, load average: 1.36, 1.13, 1.08

%Cpu(s): 1.1 us, 1.4 sy, 49.8 ni, 47.6 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
KiB Mem : 13335188 total, 9313584 free, 1118076 used, 2903528 buff/cache
KiB Swap: 0 total, 0 free, 0 used. 12109812 avail Mem


421 root 30 10 550100 416388 7500 S 99.3 3.1 297:28.68 mprime
416 root 20 0 36.335g 94060 82872 S 0.7 0.7 2:08.60 mfaktc.e+
127 root 20 0 653980 152760 62208 S 0.5 1.1 1:46.18 python3
27 root 20 0 404180 100632 26152 S 0.1 0.8 0:29.97 jupyter-+
358 root 20 0 1388332 58440 25740 S 0.1 0.4 0:18.73 drive
9 root 20 0 691856 62776 24940 S 0.0 0.5 0:15.48 node
119 root 20 0 35884 4932 3840 S 0.0 0.0 0:02.87 tail
404 root 20 0 4568 876 812 S 0.0 0.0 0:00.66 tail
1 root 20 0 39192 6548 5044 S 0.0 0.0 0:00.04 run.sh

[/CODE](No complaints, just have never seen it do that before.)

Lifetime limits?
 

So, yesterday Dylan managed to get a Colab session, which appears to have lasted about ten hours. Today, Storm got one; running currently.

None of my five different accounts have received a GPU backend for about a week now, nor anyone else with the exception of Wayne.

This tells me that while Colab have not blocked the GPU72_TF Notebook specifically, it does appear there is some kind of a "lifetime" GPU quote. It will be interesting to observe what happens to others doing GPU work in the future.

Very much a black box...

[QUOTE=chalsall;535232] with the exception of Wayne...[/QUOTE]

Colab: A couple days ago your Code stopped failing for me (post 788). But I haven't been able to get a GPU in those 2 days.

Kaggle: I consistently get my 30+ hours every week without fail.

I only run mfaktc via the code you provided

[QUOTE=chalsall;535232]None of my five different accounts have received a GPU backend for about a week now[/QUOTE]

Do you run CPU-only work when you don't get a GPU backend? If not, can you (on the theory that this will help the Google overmind unlearn your usage pattern)?