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-   -   Distributing gpu-ecm curves to multiple cpu-workers (https://www.mersenneforum.org/showthread.php?t=24462)

SethTro 2019-05-24 07:37

Distributing gpu-ecm curves to multiple cpu-workers
 
I'm taking a stab at ECM for a c251 (home prime 49 step 119) with t65.
it's been tested to 2*t60 so I'm starting at t65 (b1=850e6, b2=1.4e13, ~80k curves)

I have 2x1080ti and a 32 core machine (2x E5-2650 v2).
on cpu, stage 1 takes ~7200s/curve, stage 2 takes ~1800s/curve.
on gpu, stage 1 is much faster (10x? 20x?)

Ideally I would like to do a ton of stage 1 calculations on gpu and then distribute those to the cpus for stage 2.

Do I just pass `-save curves_<worker> <b1> 0` to the gpu worker then
`-resume curves_<worker> <b1> <b2>` to each cpu worker?

chris2be8 2019-05-24 16:22

That's about right, but you need to split the save file to give each core running stage 2 separate lines from it.

Here's part of a script I use to run ECM to 35 digits. On this system I need 3 cores to run stage 2 as fast as the GPU does stage 1, you will probably need to change that.
[code]
#!/bin/bash

function do_block
{
B1=$1
/home/chris/ecm.2741/trunk/ecm -gpu -save $NAME.save $B1 1 > $INI | tee -a $LOG
wait # for the last stage 2 to finish
grep -q 'Factor found' $LOG* # Check if we found a factor
if (($?==0));then exit 0;fi
rm $NAME.saveaa $NAME.saveab $NAME.saveac
split -nl/3 $NAME.save $NAME.save
rm $NAME.save
(nice -n 19 /home/chris/ecm.2741/trunk/ecm -resume $NAME.saveaa $B1;/home/chris/ecm-6.4.4/ecm -c 999 -idlecmd 'ps -ef | grep -q [-]save' -n $B1 <$INI ) | tee -a $LOG.1 | grep [Ff]actor &
(nice -n 19 /home/chris/ecm.2741/trunk/ecm -resume $NAME.saveab $B1;/home/chris/ecm-6.4.4/ecm -c 999 -idlecmd 'ps -ef | grep -q [-]save' -n $B1 <$INI ) | tee -a $LOG.2 | grep [Ff]actor &
(nice -n 19 /home/chris/ecm.2741/trunk/ecm -resume $NAME.saveac $B1;/home/chris/ecm-6.4.4/ecm -c 999 -idlecmd 'ps -ef | grep -q [-]save' -n $B1 <$INI ) | tee -a $LOG.3 | grep [Ff]actor &
}
[/code]Note /home/chris/ecm.2741/trunk/ecm is compiled with GPU support, while /home/chris/ecm-6.4.4/ecm was compiled with -enable-shellcmd to make it accept -idlecmd.

Chris

WraithX 2019-05-25 00:57

You should also know about the previous work that was done on this number. The last posted record is post #111 in the following thread:
[url]https://mersenneforum.org/showthread.php?t=3238&page=11[/url]

In it you can see that I had finished:
[CODE]
HP49 Step 119 c251:
Expected number of curves to find a factor of n digits:
digits 35 40 45 50 55 60 65 70 75
------------------------------------------------------------------------------------------------------
B1 = 11e6 138 788 5208 39497 336066 3167410 3.2e+007 3.7e+008
B1 = 43e6 61 278 1459 8704 57844 419970 3346252 2.9e+007
B1 = 260e6 23 82 335 1521 7650 42057 250476 1603736
B1 = 1e9 14 44 154 599 2553 11843 59619 319570
B1 = 3e9 11 31 96 335 1279 5292 23661 112329 565999
B1 = 3e9 11 31 99 344 1315 5446 24234 115138 580561 (-maxmem 4096)

Number of curves completed so far, and their equivalent t-level:
12000 @ 11e6 = 86.956x 15.228x 2.304x 0.303x 0.035x 0.003x
18000 @ 43e6 = 295.081x 64.748x 12.337x 2.068x 0.311x 0.042x 0.005x
90000 @ 260e6 = 3913.043x 1097.560x 268.656x 59.171x 11.764x 2.139x 0.359x 0.056x
120000 @ 1e9 = 8571.428x 2727.272x 779.220x 200.333x 47.003x 10.132x 2.012x 0.375x
16000 @3e9(4g)= 1454.545x 516.129x 161.616x 46.511x 12.167x 2.937x 0.660x 0.138x
19200 @ 3e9 = 1745.454x 619.354x 200.000x 57.313x 15.011x 3.628x 0.811x 0.170x
----------------------------------------------------------------------------------------------
16066.507x 5040.291x 1424.133x 365.699x 86.291x 18.881x 3.847x 0.739x
[/CODE]
ie, I finished > 3.8*t65 and > 0.7*t70.

I continued working on the number for a while splitting the work as you are planning on doing. I ended up doing a total of 162,000 curves at B1=3e9, which with the t70 recommended 112,329 curves at B1=3e9 means I did a total of 1.442*t70. You may want to start at B1=3e9, or work even higher. I'm just about to finish 1000 curves at B1=10e9, which isn't much compared to the previous effort.

When doing the work I would manually run the curves on the gpu's and then I would use my ecm.py script to spread all the finished stage-1 curves across multiple stage-2 jobs. For example, I had one gpu (I forget which) that could do 6400 stage-1 curves in 30 days, and another gpu that could do 9600 stage-1 curves in about 30 days. So, I could finish 16000 stage-1 curves per month. I would then use ecm.py to split those 16000 curves into 7 jobs (about 2286 curves per job) which could finish the work in 32 days. So, you may want to do the work in batches like this. The commands I used would look like:

[C]./ecm -gpu -gpudevice 0 -gpucurves 9600 -save g0-001_9600_3e9.txt 3e9 1 < hp49_119_c251.txt[/C]
[C]./ecm -gpu -gpudevice 1 -gpucurves 6400 -save g1-001_6400_3e9.txt 3e9 1 < hp49_119_c251.txt[/C]

And then I would combine those files into a single [C]c-001_16000_3e9.txt[/C] file and use ecm.py like so:

[C]python ecm.py -threads 7 -resume c-001_16000_3e9.txt -out r-001_16000_3e9.txt[/C]

You need to make sure you have enough memory to run 7 (or more) jobs for stage-2 with B1=3e9, otherwise your stage-2 jobs will swap and slow down drastically. I believe each job took up to 14500MB, which means the total used for those jobs on that machine was about 100GB.

You can find my ecm.py script in the following thread (the most recent version will be towards the end of the thread):
[url]https://mersenneforum.org/showthread.php?t=15508[/url]

VBCurtis 2019-05-25 04:20

This is a truly awesome amount of work! I appreciate the detail you provided of curves and t-levels. I just started the Cunningham 2_2330L factorization, which will saturate all my large-memory machines for the next season or two; I'd like to contribute some B1=1e10 curves to honor your effort, but they'll have to wait until Fall.

SethTro 2019-05-25 21:36

[QUOTE=WraithX;517691]You should also know about the previous work that was done on this number. The last posted record is post #111 in the following thread:
[url]https://mersenneforum.org/showthread.php?t=3238&page=11[/url]

In it you can see that I had finished:
...
[/QUOTE]


Thanks for the status update! I had seen your 2014 status from [url]http://worldofnumbers.com/topic1.htm[/url] but hadn't searched here.


[QUOTE=WraithX;517691]
You need to make sure you have enough memory to run 7 (or more) jobs for stage-2 with B1=3e9, otherwise your stage-2 jobs will swap and slow down drastically.
[/QUOTE]

Again thanks for the detailed report, why the "7 (or more)"?

Do you know of a write-up of the performance impact of using -maxmem? I did several searches but didn't find anything definitive (other than non-linear: [url]https://www.mersenneforum.org/showpost.php?p=501860&postcount=52[/url])



[QUOTE=WraithX;517691]
You can find my ecm.py script in the following thread (the most recent version will be towards the end of the thread):
[url]https://mersenneforum.org/showthread.php?t=15508[/url]
[/QUOTE]

I'm already using your wonderful script. I did have to make a couple of modifications to make it work with python3 (I'll try and post a patch later).

Since you seem to be actively working on this, what curves would be most useful for me to work on? I'm willing to spend a 1080 GPU-month + a couple core years with high memory.

WraithX 2019-06-01 04:14

[QUOTE=SethTro;517773]Again thanks for the detailed report, why the "7 (or more)"?[/QUOTE]

I used 7 because I was able to run that many jobs on a machine with 128GB of ram. You'll need to calculate how much ram a job will take (with or without maxmem) and then figure out how many you can run in parallel.

[QUOTE=SethTro;517773]Do you know of a write-up of the performance impact of using -maxmem? I did several searches but didn't find anything definitive (other than non-linear: [url]https://www.mersenneforum.org/showpost.php?p=501860&postcount=52[/url])[/QUOTE]

I don't really know of a write-up on the performance impact of using -maxmem. The only thing I know is that it will reduce the B2 value and increase the k value (internal gmp-ecm variable), which will slightly decrease the odds of finding a factor and somewhat increase the stage-2 runtime. You can use the -v option to see the impact of various -maxmem options. ie, Look for the "estimated number of curves to find a factor of n digits" table. This will let you know how many curves to run at the given B1 value to have a [$]1 - 1/e^x[/$] (where x = curves_run/recommended_curves) chance of finding a factor of the specified size (if one exists).

For example, using B1=11e6 without maxmem will look like:
[code]
Using B1=11000000, B2=35133391030, polynomial Dickson(12), sigma=1:2580904028
dF=32768, k=3, d=324870, d2=11, i0=23
Expected number of curves to find a factor of n digits:
35 40 45 50 55 60 65
138 788 5208 39497 336066 3167410 3.2e+007
[/code]
And with maxmem 20 it will look like:
[code]
Using B1=11000000, B2=28545931060, polynomial Dickson(12), sigma=1:3439101351
dF=8192, k=40, d=79170, d2=11, i0=128
Expected number of curves to find a factor of n digits:
35 40 45 50 55 60 65
142 813 5420 40914 348634 3290145 3.4e+007
[/code]
And with maxmem 40 it will look like:
[code]
Using B1=11000000, B2=28544268490, polynomial Dickson(12), sigma=1:2669738918
dF=16384, k=10, d=158340, d2=11, i0=59
Expected number of curves to find a factor of n digits:
35 40 45 50 55 60 65
142 813 5420 40914 348634 3290145 3.4e+007
[/code]

You can see that maxmem decreases the B2 value and increases the k value, so you get slightly lower odds of finding a factor and somewhat longer runtimes.
In this case if you ran 10000 curves at B1=11e6 with no, 20, or 40 maxmem, your odds of finding various sized factors would be:
[code]
Chance to find factor, of size d, = 1 - 1/e^x, where x = 10000/recommended_curves
d 35 40 45 50 55 60
no ~100% 99.9996% 85.341% 22.367% 2.931% 0.315%
20 ~100% 99.9995% 84.197% 21.683% 2.827% 0.303%
40 ~100% 99.9995% 84.197% 21.683% 2.827% 0.303%

Chance to miss factor, of size d, = 1/e^x, where x = 10000/recommended_curves
d 35 40 45 50 55 60
no ~0% 0.000308% 14.658% 77.632% 97.068% 99.684%
20 ~0% 0.000455% 15.802% 78.316% 97.172% 99.696%
40 ~0% 0.000455% 15.802% 78.316% 97.172% 99.696%
[/code]

[QUOTE=SethTro;517773]I'm already using your wonderful script. I did have to make a couple of modifications to make it work with python3 (I'll try and post a patch later).[/QUOTE]

Thanks. I've been patching over the years, but haven't posted an update in a while. I'll post the update, with some of your changes, here in a bit.

[QUOTE=SethTro;517773]Since you seem to be actively working on this, what curves would be most useful for me to work on? I'm willing to spend a 1080 GPU-month + a couple core years with high memory.[/QUOTE]
"Active" is subjective. I haven't really worked on this since Nov 2017. I think it was the 1080 that could complete 9600 stage-1 curves with B1=3e9 in ~30 days. My computers are busy, so you'll have to verify this on your own machine. I'd recommend running with B1=3e9 or higher.

SethTro 2019-06-01 15:47

Thanks for the information.

I did a little investigation of maxmem by myself between when I last posted and now.

[url]https://docs.google.com/spreadsheets/d/1D1nod6qbSI0v56OsLeolhwYb-R2VJ-RPXpwbajAO6R4/edit?usp=sharing[/url]

[url]https://github.com/sethtroisi/misc-scripts/tree/master/ecm-maxmem[/url]

The result is that it linearly slows down on stage 2 while slightly reducing B2 (about 10% on average).
If ecm would use 16000 MB by default, and I set maxmem=4000MB then I expect stage 2 to take 4x as long!


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