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Jim Hunt

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The Distributed Arctic Sea Ice Model
« on: March 09, 2013, 10:23:50 PM »
Just in case I can interest anyone in the concept when I'm at The Arctic Summit on Tuesday, I've set up a placeholder open source project on Google Code, catchily entitled "The Distributed Arctic Sea Ice Model", or DASIM for short.

Any questions?
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Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #1 on: March 10, 2013, 12:11:58 PM »
I was toying with the idea of handing out a "flier" to anyone in Oslo who might be interested. This is what I've come up with so far:

http://econnexus.org/dasim

What does the team think?
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crandles

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Re: The Distributed Arctic Sea Ice Model
« Reply #2 on: March 10, 2013, 12:49:12 PM »
How would a flyer do the 'during' video part?

I am not sure what you are planning on doing. It sounded like you might be able to tweak initial conditions but if you are just running the models with tweaked initial conditions, that is just an initial condition ensemble with an existing model. Why would a group unfamiliar with the model do better than the researchers who have extensively studied what works with the model? Tweaking the coding of the model or even just adjusting parameters rather than initial conditions is going to require pretty deep understanding of the model.

A collaborative effort sounds good and I don't want to be overly critical. However, I suggest there has to be some realistic aim that can be fulfilled, ideally the aim should be one where 'we' are better able to do it than anyone else. I think we would need a lot of knowledge of a model before we come anywhere close to that. Models can easily be half a million lines of code so are very complicated beasts.


'we' - err,  who am I kidding? I wouldn't be any use despite a fair amount of knowledge about CPDN (for a participant cruncher).

Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #3 on: March 10, 2013, 02:03:57 PM »
A hasty first draft of a "flier" is at the bottom of that page now Crandles, albeit without any "video"!

What do you reckon?
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crandles

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Re: The Distributed Arctic Sea Ice Model
« Reply #4 on: March 10, 2013, 06:05:09 PM »
Quote
The existing models can't tell you.

This one can (real soon now!)

What justifies that you will be able to something that other models have failed to do? If you believe you have something then this should be explained somewhere. Otherwise how do you justify that not being a bit insulting to modelers?


crandles

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Re: The Distributed Arctic Sea Ice Model
« Reply #5 on: March 10, 2013, 08:43:25 PM »
I asked a few questions over on a CPDN board. Another moderator, Mo, seemed to agree with my assessments given above. She added a few thoughts:


Quote
Probably very hard ... Well, NASA is having a hard time. The Met Office has been bashing away at the Unified Model for two decades if I'm not mistaken.


If they need any help with the modelling, here's a link to to the climateeducation course:

http://reciprocatesite.conted.ox.ac.uk/

Say that you have to take Part 1 of the course first and can then go on to Part 2 which is intended for people who wish to learn to implement PRECIS regional modelling. Tell them that the Met Office runs short courses for people who want to set up their own regional models using PRECIS. Mostly the people who attend these courses are meteorologists in their own countries but they might be accepted by the Met Office if they've taken the course and are proficient in Linux.

I suspect that second course would only be relevant if you decided on using the PRECIS regional model.

I am sure you can find the CPDN site to look for very basic introductions like
http://climateprediction.net/content/modelling-climate
but the reciprocate site link above looks more relevant.

Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #6 on: March 11, 2013, 01:17:37 AM »
Hi Crandles,

I've just arrived in my hotel room in Oslo, after a long days travelling. There was a torrential downpour of sleet as I headed up the M5, which had turned to gentle flurries of snow by the time I got to Bristol Airport.

The language you have reservations about was an attempt to draft something that might catch the attention of any business types I might be able to hand a piece of paper to on Tuesday, and at least persuade them to click a link or two.

What would you suggest instead?  I have no pretentions about being (or becoming) a climate modeller by the way. I do program computers for a living though. Any climate modelling expertise that the project might ultimately include would need to come from elsewhere.
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crandles

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Re: The Distributed Arctic Sea Ice Model
« Reply #7 on: March 11, 2013, 03:50:18 AM »
I would be pushing an impacts study:

Models are doing poorly at predicting when seasonally sea ice free and different methods get large range of answers. By? 2050 Ref. 87% on Neven's forum think before 2020! Even if not all experts are convinced it will happen this decade, with models doing so badly, some preparation is a sensible precaution.

We should be running climateprediction.net / weather @ home type simulations where ice melts out during summer to see what adverse weather becomes more common. Northern Hemisphere countries are running short of time if the conclusions suggest we should build more dams to cope with longer droughts because planning and building take time. Similar situation for flood defenses.

Note: maybe I am only at the stage of wondering if such a project is feasible.

The vastly different timescale between 2015 and 2050 seems worth drawing attention to.

Sorry if you are out of time to draft or do anything with this and for mis-understanding what you wanted.

Artful Dodger

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Re: The Distributed Arctic Sea Ice Model
« Reply #8 on: March 11, 2013, 04:19:26 AM »
What would you suggest instead?  I have no pretentions about being (or becoming) a climate modeller by the way. I do program computers for a living though. Any climate modelling expertise that the project might ultimately include would need to come from elsewhere.

Hi Jim,

Science always proceeds in 3 Stages:
  • Description
  • Prediction
  • Understanding
It's pretty clear from the dismal modeling results to date that we are firmly stuck at Stage 1.

What I would suggest is a statistical approach to sea ice description. Enumerate all the physical factors that effect sea ice. Create a huge covariance matrix. Find all correlation coefficients, and identify any factors that show either strongly positive and strongly negative correlations.

Produce a single equation in the form of a multiple regression that describes the progress of arctic sea ice evolution over the last 34 years. When this equation produces a lower standard error than the best models, it's time to restart modelling efforts.

But now, we would know which physical parameters to model. And we'd know which data needs to be collected. At that point, we could predict sea ice (the 'dependent variable') based on observations of the known independent variables. That's Science.

Good luck in Oslo! We could use some good luck at this point. Even 1997 would have been tight...  :'(
« Last Edit: March 11, 2013, 04:28:10 AM by Artful Dodger »
Cheers!
Lodger

Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #9 on: March 11, 2013, 11:35:21 AM »
@Crandles - Unless I misunderstood, you suggested previously that CPDN don't seem to be amenable to running the sort of tests you'd like to see happening?

Beyond that Lodger seems to be suggesting that something fundamental must be missing from the current models? Even cloning CPDN for our own purposes wouldn't necessarily get us a whole lot further?

Whilst we ponder those imponderables, here's my current IT setup for the Arctic Summit here in Oslo. Please note the Raspberry Pi running CICE, albeit only for 1997. Those were the days!

http://econnexus.org/projects/the-distributed-arctic-sea-ice-model/sea-ice-pie/

P.S. TypePad's self references don't seem to be working properly  :(
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crandles

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Re: The Distributed Arctic Sea Ice Model
« Reply #10 on: March 11, 2013, 01:45:37 PM »
@Crandles - Unless I misunderstood, you suggested previously that CPDN don't seem to be amenable to running the sort of tests you'd like to see happening?


I don't think they have given it much if any serious consideration. Ideas need expert consideration to ensure the best ideas are pursued. So listening to amateurs isn't really the done thing. If I thought it had been considered and was not suitable then I would accept that and not be thinking of trying to push it.

To me, it seems that modelers believe their models telling them dates of 2040 ish. While many of us believe the volume extrapolations, I think both we and modelers should accept there is some uncertainty. If there is uncertainty then preparation should ideally be in time for the earliest date. We have gone past that so it looks to me like it deserves some pushing.

I am not sure how to do that pushing effectively. Modelers seem not to believe the level of uncertainty in the timing. As for politicians, I see examples of scientists telling them we need to consider earlier dates and this being waved aside based on earlier advice that it won't happen before 2030. An example of hearing what they want to hear: In a way politicians do not want to act rashly and find it was unnecessary. Far better for them to rely on old advice as the reason they didn't do much. Encouraging further research to see how much action might be required seems a sensible message that could be sold to them. However, whether they would take action to direct funding bodies to fund suitable research or stick to a rely on earlier research to absolve themselves approach isn't clear to me.

Is this situation a disaster waiting to happen with no-one taking action or even research? Some people almost seem to be hoping for a disaster to kick the population into action. I don't want to join that club nor try to push inappropriate research so I am trying to air the idea for reaction.




Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #11 on: March 24, 2013, 11:11:49 AM »
Quote
https://forum.arctic-sea-ice.net/index.php/topic,108.0.html

which would seem to be the best place to continue this discussion. You'll see that RasPi clusters do get a mention!

Don't see any talk of clusters , just you Pi experiment Olso.

What did I miss?


Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #12 on: March 24, 2013, 01:12:12 PM »
Sorry Kim.

On sober reflection my language was somewhat confusing! I was referring to the "Lego" link on the thread you have arrived from to the University of Southampton's "Raspberry Pi Supercomputer"
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Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #13 on: March 24, 2013, 07:38:30 PM »
Thanks Jim, interesting link.

Most of the power of pi is in the GPU, not sure how much use that would be in the context of a cluster.

Cross-platform code like CICE won't take advantage of it without some specific, l33t recoding.

I've always fancied building a linux cluster but never had the need/motivation.  If I did, I'd probably chose something better than Upton's finger-in-a-pie.


Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #14 on: March 26, 2013, 11:52:26 AM »
My pleasure Kim,

I don't suppose you happen to know an expert in "specific l33t recoding" do you?

I haven't run any benchmarks yet (unless you count CICIE itself) but the Raspbian flavour of GNU Fortran is reputed to use "hardware floating point" at least.
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Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #15 on: March 26, 2013, 02:14:53 PM »
Well if they have gone that far with Ripian it maybe worth a second look.

That means there is sufficient specific support for whichever ARM core they are using for it to be using the FPU.  That means GCC is well tuned to that hardware platform.

Since these chips are contending for mobile market their devs have an interest in cooperating and ensuring they get gcc support.

I saw some time ago discussions of using GPU as well.  Sadly that's R-Pi starts to fall down. All that is in the FPG array the code of which is a propitiatory binary file. No way is anyone going to get the slightest info on what that does, let alone code.

That's why I got disinterested in playing with Pi.  So much of the hardware of Pi is effectively closed source firmware implemented on chip, it shuts you out.

I don't think the Broadcom chip was a very good choice in that respect but since Upton works for them, the whole project is a marketing exercise for them all wrapped up as a non-profit educational project, anyway.

A more open platform would have had more educational value.

But all in all it's going to bring the price of these devices down which is nice.


If CICE is what you want to run, I would say the makes it the most suitable benchmark.

I would suggest taking step back and defining what you aims are before getting to much time on implementation detail.

Processing power per watt is good on Pi but you don't really need a full blown linux desktop if you want to build a number crunching cluster.

I would give close thought to how the cluster will run. The Southampton project uses some high level messaging system that looks rather inefficient and requires programming in a specific language. Don't think it would run CICE.

There are hundreds if not thousands of these small ARM/Cortex etc boards now. I suspect there's better options than Pi, but you'll need to define objectives to make the right choice.

HTH.


Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #16 on: March 26, 2013, 11:54:42 PM »
Hi Kim,

My main aim at the moment is to get some input from someone vastly more experienced at climate modelling than me!

The "Soton supercomputer" uses MPI, and as luck would have it CICE uses MPI too, for both internal parallelisation and external coupling.

Broadcom marketing exercise or not, the RasPi certainly has a high profile and a large fan club, here in the UK at least.

« Last Edit: March 27, 2013, 10:58:47 AM by Jim Hunt »
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Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #17 on: March 27, 2013, 12:59:16 AM »
Quote
CICE uses MPI too,


That's a stroke of luck. ;)  I'd been reading the doc on CICE but I was more interested in the physics than the coding interface.

That should make it reasonably easy (depending upon skill set) to make it run on a pot of Raspberry jam.

You'd probably want to build a stripped down linux or at least set up a run level that doesn't start the gnome desktop and all its widgets.  I built a lightweight linux for ARM as a data logger and controller for my solar water heater, that takes up 16MB .

You'll want to cut out some of the cruft from Ripian I would expect.


I was a bit shocked in the video when he said it had cost 4K to put together. He also mentions Mips though-put so that may give a first guess at whether it would be in the ball park for running CICE.

a high profile and a large fan club is more an accolade to their marketing than its technical merit. The concept is great and it has been well received. But as soon as you want to do more than blink a couple of LEDs you need the Gert Board and that costs more than the Pi itself.

I was thinking of using it for an embedded project I wanted to do but quickly realised it was far too limited and inflexible in hardware terms.

Have you got access to recent CICE versions? There 4.1 is from 2010 and must be pretty out of data by now.  I don't know how accessible they are to giving access to "trunk".

Jim Hunt

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« Last Edit: March 27, 2013, 01:29:57 PM by Jim Hunt »
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Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #19 on: March 27, 2013, 02:00:27 PM »
thanks. No useful CICE links in there but a link to MODTRANS is useful. It used to be on Dr. Archer's site but it got removed.


That was where I initially got interested in climate many years ago. He used it to point out just how small a change in radiation any change to atmospheric CO2 in either direction would make. Quite an eye opener for me at the time.

How many Pi's do you think would be required to run CICE at a useful resolution?


Robert Marston

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Re: The Distributed Arctic Sea Ice Model
« Reply #20 on: March 27, 2013, 04:17:16 PM »
This project is just begging to be crowd sourced.

Cloud computing to run the model tweaks and test against real time for accuracy (instead of supercomputers).
Web page to provide basic definitions/links to source code sites/model descriptions and history of model accuracy and use.
Outreach to university professors to ask students to submit different variations of the models (multiple projects, worldwide, hopefully).
Method for individuals small teams to submit tweaks to computer models.
Possible industry participation (re-insurers other concerned parties).

A sort of model source code and analysis freeware/cloudware that everyone owns, everyone can participate in, and everyone can track the results from designed to aid/facilitate the work being done at the world's major climate offices.

I don't know if it will be successful. We do have weather models that are very accurate where they used to be less so. And I think that those evolved as weather dynamics became better and better defined. Ice is different. We don't have many eyes on the ice when compared to weather. We don't have so many people tracking it and identifying factors that influence melt. Same with global climate change. Still a pretty esoteric and ill understood process. I think broadening the base of work/interest might be a lot of help to the scientists as seems to have been the case with general weather.

???
« Last Edit: March 27, 2013, 04:27:04 PM by Robert Marston »

Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #21 on: March 27, 2013, 04:59:10 PM »
Quote
This project is just begging to be crowd sourced.

Good idea. Something like Boinc project years ago to rum global models or yeti@home  ;)



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Re: The Distributed Arctic Sea Ice Model
« Reply #22 on: March 27, 2013, 05:04:48 PM »
This project is just begging to be crowd sourced.

I completely agree with this point. Also I like the idea how people are involved. Sounds much more inspiring than searching aliens or folding proteins. I have implemented 2 or 3 distributed business models and have a single advice: Get the absolute minimum thinkable running (server + client), from that point update often and early. Which means get to the heart of the problem, drop drift, salt, declination, floes, ice age, brines, leads, polynyas, seasons, ozone, etc..

And as a part time programmer: Don't spend time with existing sea ice models, they do not support parallel execution (I'd prefer to be wrong at this point), which basically means all code is unusable. Good for inspiration on how to implement a formula, but no copy&paste of structure or information flow. Single machine code is fundamentally different from multiple machines code.

I wish, I had currently more time, may be next winter, w'd love to work on an webgl interface.

"Every software should get developed top down, except for the first time"

NeilT

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Re: The Distributed Arctic Sea Ice Model
« Reply #23 on: March 27, 2013, 05:23:56 PM »
I have some experience playing with Linux password hash crackers using GPU.  Sadly no experience in coding them as I've pretty much given up coding.

The interesting point is that AMD grapics cards are roughly 1.5 - 2 x faster than Nvidia for these kind of operations and also that the latest quad AMD grpahics gpu crackes are  hitting more than 9 BILLION hash checks per second.

folding@home uses gpu for this too.

Whilst Grid/CPU is a good solution for some things, smaller clusters of GPU machines could be much more viable for this kind of project.

Just a thought.

Whilst I was looking around

Whilst looking around I came across this

Quote
I noticed a Performance increase of about 1000%

 using a GPU even for common problems like searching
Being right too soon is socially unacceptable.

Robert A. Heinlein

Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #24 on: March 27, 2013, 05:29:31 PM »
Hi Robert,

This project is just begging to be crowd sourced.

Perhaps at this juncture I might refer you back to the genesis of DASIM on another thread/venue:

https://forum.arctic-sea-ice.net/index.php/topic,51.msg462.html#msg462

and before that on the ASI blog.

« Last Edit: March 27, 2013, 05:37:35 PM by Jim Hunt »
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Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #25 on: March 27, 2013, 05:45:38 PM »
Hi Arctic.io,

As luck would have it CICE does support MPI, but maybe that's not the sort of "parallel execution" you had in mind?

Thanks also for your support for the concept. Moral is great. Physical is even better!
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Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #26 on: March 27, 2013, 05:48:45 PM »
Hi Neil,

Now all we need is to find a large pile of GPUs sitting around doing nothing!

Oh, and a climate modelling guru or two too.
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Re: The Distributed Arctic Sea Ice Model
« Reply #27 on: March 27, 2013, 06:03:46 PM »
Quote
Now all we need is to find a large pile of GPUs sitting around doing nothing!

A large proportion of the GPU's on the planet are doing sod all. ;)

What's yours doing right now? Not much I would guess.

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Re: The Distributed Arctic Sea Ice Model
« Reply #28 on: March 27, 2013, 07:02:58 PM »
The reason I mentioned the old SETI project on the other thread is it linked computers to run analysis during down time. You go to sleep, it cracked away running an analysis program. Perhaps something similar with a crowd sourced climate model? A program you could download in order to donate your computer's downtime.

I see the links. Will go and look at those threads now.

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Re: The Distributed Arctic Sea Ice Model
« Reply #29 on: March 27, 2013, 08:19:09 PM »
As luck would have it CICE does support MPI, but maybe that's not the sort of "parallel execution" you had in mind?
MPI is same machine multiple threads. The controller can expect to get results in time. With a distributed model, you have no control when results come back, might be minutes, might be months, might be never. The challenge is to split the problem into _completely_ independent tasks. With proteins you split on proteins, with aliens you split on planets. With sea ice, umh, may be different parameters, so each client number crunches his own ice pack, essentially a different planet too. That would give you members to build an ensemble and get an average. So clients may use MPI locally, a distributed model can't.

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Re: The Distributed Arctic Sea Ice Model
« Reply #30 on: March 27, 2013, 09:54:58 PM »
Quote
MPI was designed for high performance on both massively parallel machines and on workstation clusters.

The Southampton Uni R-pi cluster was also separate machines with single cores.

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Re: The Distributed Arctic Sea Ice Model
« Reply #31 on: March 28, 2013, 09:07:15 AM »
OK, MPI moved on since last time I checked. However, from what I've read yesterday most applications rely on a constant number of processes. So may be a definition of what 'distributed' in this context means might help to sort out issues. Am I right by assuming even clients running only during the night on an unstable dial-up connection from Greenland can participate?

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Re: The Distributed Arctic Sea Ice Model
« Reply #32 on: March 28, 2013, 06:02:23 PM »
http://www.google.fr/url?sa=t&rct=j&q=&esrc=s&source=web&cd=10&ved=0CHMQFjAJ&url=http%3A%2F%2Fwww.nceo.ac.uk%2Fdocuments%2FNCEO2011_Flocco_Schroeder_Feltham.pdf&ei=-WlUUdLOMsOYO6CwgeAG&usg=AFQjCNF3RGQ6NDMz8Emn1hQ5NKqf17Bi5w&bvm=bv.44342787,d.ZWU

Just found this, Flocco paper explaining CICE melt pond addition .
esp. see fig 7

CICE does not produce the major drop from 1990's to 2007 at all :( 
Shorter variation not bad at all. All that seems to be achieved by the melt pond saga is to drop the overall levels so that  the model matches better towards the end and less well at the beginning.

Annual variation was not enough without ponds but it too much with ponds.
Of the bunch, the Flocco model seems better than its predecessors though.

This suggests to me that there is a major external influence causing the post 1990 decline that is not in the model.

I'm also suspicious of why for a 2010 paper they chose to stop comparisons in 2007. My guess is that it fairs very poorly with the more recent annual swings.

Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #33 on: April 03, 2013, 03:14:52 PM »
Do you suppose there's any chance we could persuade Los Alamos to lend us Roadrunner for a while?

http://www.bbc.co.uk/news/technology-21993132

Quote
A US supercomputer called Roadrunner has been switched off by the Los Alamos National Laboratory in New Mexico.

The machine was the first to operate at "petaflop pace" - the equivalent of 1,000 trillion calculations per second - when it launched in 2008.
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Ice Cool Kim

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Re: The Distributed Arctic Sea Ice Model
« Reply #34 on: April 03, 2013, 03:29:12 PM »
just one of those cabinets would do the job. Since they're breaking it , may be make an offer. What's per ton scrap value? Probably affordable  :)

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Re: The Distributed Arctic Sea Ice Model
« Reply #35 on: April 03, 2013, 03:31:31 PM »
Jim , have you asked for access to the recent version of CICE code repository? I have not even had the pleasure of a refusal.

v4.1 is OK for seeing whether you can run it but it's way out of date in terms of the model.


Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #36 on: April 03, 2013, 06:08:00 PM »
Hi Kim,

I have the CESM source code also, which includes CICE amongst a host of other things. The source for that version does look rather different to the original Los Alamos version.

However I've also spoken to a couple of people who should know what they're talking about, and they assure me 4.1 is the latest "stable" release. In "a coordinated international effort" CESM take it and modify it in order to couple it to their GCM. The Hadley Centre take it and experiment with modifications to the thermodynamics. The US Navy take it and modify other portions of it, etc. etc.

Re Roadrunner, I've no idea what the scrap value of each cabinet might be. However I suspect that the cost of the electricity needed to run all those GPUs and the associated air conditioning units for a significant length of time would be significantly greater than zero!
 
« Last Edit: April 07, 2013, 02:16:11 PM by Jim Hunt »
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Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #37 on: April 04, 2013, 03:47:27 PM »
Re your Flocco/CICE melt pond query Kim, I am informed that:

"[They chose to stop comparisons in 2007] because some forcing data was only available through 2007 at the time [they] did the runs. Then it takes some time to get a paper through the review process and into print."

Given the current empirical data hot off the presses from the real world, perhaps it wouldn't come as too much of a shock should one discover that the CICE model is much more sensitive to forcing data than to internal model parameters. By way of example see this 2011 "poster" from Los Alamos. Unfortunately the learned papers referenced seem to be paywalled.
« Last Edit: April 04, 2013, 05:10:20 PM by Jim Hunt »
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Re: The Distributed Arctic Sea Ice Model
« Reply #38 on: April 07, 2013, 02:07:58 PM »
An additional contribution to the debate from A-Team over in the PIOMAS April 2013 thread on the ASI blog:

Piomass solves the 'ice momentum equation governed by a viscous–plastic rheology with an elliptical plastic yield curve" as described in Hibler 1979, which in turn is based on the AIDJEX model of Coon 1974. The Los Alamos CICE sea ice model Hunke and Lipscomb 2008 also uses a very similar isotropic elastic-visco-plastic rheology.

At the time, these improved on primitive rheologies assuming a freely drifting, compressible viscous Newtonian fluid with zero shear strength ice pack However VP isotropic rheology cannot and does not capture observed shear, vorticity, divergence, thickness distributions, trends in velocity and export, or deformation-driven ice production.

Looking through the rear view mirror for 'Inside Baseball' statistics will not get at the ice end game at all. This is just 'negotiating' in Kübler-Ross terms -- denial, anger, negotiating etc have no effect on actual outcome.

Jerome Weiss. Drift, Deformation and Fracture of Sea Ice SpringerBriefs in Earth Sciences DOI: 10.1007/978-94-0007-6202-2.5

http://192.95.52.196/wordpress/wp-content/uploads/2013/02/Paper5EarlyView.pdf
« Last Edit: April 07, 2013, 10:08:41 PM by Jim Hunt »
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Re: The Distributed Arctic Sea Ice Model
« Reply #39 on: April 10, 2013, 02:15:23 AM »
Here is Martin O'Leary's introduction of his Javascript Ice Sheet Model. I know, it is not about sea ice, on the other hand he introduces a possible technology actually needed to really allow distributed computing. There are apprx. a billion machines on this planet capable of running Javascript.

http://lists.cryolist.org/pipermail/cryolist-cryolist.org/2013-February/001969.html

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Re: The Distributed Arctic Sea Ice Model
« Reply #40 on: April 12, 2013, 10:04:33 PM »
Here is Martin O'Leary's introduction of his Javascript Ice Sheet Model. I know, it is not about sea ice, on the other hand he introduces a possible technology actually needed to really allow distributed computing. There are apprx. a billion machines on this planet capable of running Javascript.

http://lists.cryolist.org/pipermail/cryolist-cryolist.org/2013-February/001969.html
I'm curious how you'd persuade people to keep their browser windows open while it runs though (or to even open them in the first place)? Javascript is also subject to rather tight security constraints - though if you only need to communicate back to the server that shouldn't be problematic in itself. It's not what I'd call a high performance language... and implementations vary.

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Re: The Distributed Arctic Sea Ice Model
« Reply #41 on: April 12, 2013, 11:09:40 PM »
ccgwebmaster, don't understand first point, if you want to run a program, you'll keep the window open, otherwise you'll close it.

I see the security constraints as an advantage, users can be sure the program doesn't go wild, because it runs in a sandbox.

WebRTC is a recent web standard and allows communication directly between (different) browsers, basically you can use it to program your own Skype version or exchange any kind of data.

And performance is getting better, since running a model is just number crunching you can assume 50% native speed, which means you only need to double the number of nodes to achieve C or Fortran like performance. Given the amazing number of possible clients that's my last concern.

Here is a simple implementation of the Navier Stokes equations, try for yourself : http://nerget.com/fluidSim/

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Re: The Distributed Arctic Sea Ice Model
« Reply #42 on: April 12, 2013, 11:33:24 PM »
ccgwebmaster, don't understand first point, if you want to run a program, you'll keep the window open, otherwise you'll close it.
If you want to use distributed computing resources, I'd argue you don't want that model (which I grant is how most people see running programs). You'd do better with something that can run around the clock in the background, potentially even just using idle CPU resource when the machine isn't doing a lot else. The person running the program need never be aware it exists and never usually see any "window" at all. That would arguably be more likely to give access to a much larger resource.

Just strikes me there's a world of difference between however many people remembering to open a browser window to run some javascript for as long as they feel like vs something that is always running without any thought of effort on their behalf - and most likely using a much more robust and high performance platform than javascript.

The fine art of optimisation is something that really gets lost these days - as there is so much processing capacity available on the typical machine that nobody really considers it a problem to be very wasteful of it. In some situations truly dramatic optimisations can be obtained by just improving a piece of code. If one can optimise something by, say, 100x by improving the code (or platform) - you need to recruit an awful lot more people to balance that! (and I have in the past achieved optimisations of that magnitude or greater - though not necessarily in raw computation scenarios of the type being mentioned here)

Do you have any reference that doubling the nodes is enough to get C/Fortran like performance? (I'd have expected Javascript to be significantly worse than that)

The example you provide is interesting (setting aside the efficiency issue with the CPU resource), as is WebRTC. I view Javascript as a lightweight (frequently unreliable) addition for web development whereby you can move some processing client side to save a server round trip and provide a faster response, typically with UI elements. For anything more than the most superficial functionality I'd go straight to C# or T-SQL (and in the past Delphi or VB), while noting none of them is necessarily ideal for heavy computational processing either.

If you could farm out the computation tasks appropriately, I suppose there's an argument for being able to provide both approaches - javascript for people casually dipping into it, and encouraging them to install a proper platform via that route?

I do applications and databases, I don't know a lot about the sorts of calculations that would be involved in modelling - never had the need/opportunity to date to get into that sort of thing. I assume they lend themselves very well to parallelism?

ccgwebmaster

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Re: The Distributed Arctic Sea Ice Model
« Reply #43 on: April 12, 2013, 11:48:39 PM »
And performance is getting better, since running a model is just number crunching you can assume 50% native speed, which means you only need to double the number of nodes to achieve C or Fortran like performance. Given the amazing number of possible clients that's my last concern.
Incidentally performance wise, I'd tip the comments earlier in the threat mentioning the use of idle graphics cards. I believe that's what (at least until very recently) bitcoin mining rigs (where rate of calculations is critically important) were using. You won't tap into that using javascript to my knowledge - it's native hardware stuff - you need the proper access to the hardware which the javascript sandbox won't let you anywhere near.

Performance probably an order of magnitude or two better, I suspect (one should consider just how many layers of abstraction javascript is adding onto the hardware before it executes a single line of code). Javascript isn't even strongly typed! (OK, I'm biased - I regard javascript as little better than a toy language - but I have some good reasons not to care much for it)

No reason I can see one can't do distributed computing of this sort in theory - already been done:
http://setiathome.berkeley.edu/
http://www.bbc.co.uk/sn/hottopics/climatechange/moreaboutexperiment.shtml

You just need the platform - and the program.

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Re: The Distributed Arctic Sea Ice Model
« Reply #44 on: April 13, 2013, 12:15:39 AM »
I do applications and databases, I don't know a lot about the sorts of calculations that would be involved in modelling - never had the need/opportunity to date to get into that sort of thing. I assume they lend themselves very well to parallelism?

Not sure about ice models. For weather/climate, while the same calculations are performed for all cells including adjacent ones, the problem is access to information from adjacent cells. A large cache helps. While GPU can do lots of calcs in parallel, can you get the information there in a timely fashion?


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You just need the platform - and the program.

BOINC is a open source platform used by many distributed computing projects including Seti, CPDN and many more. I think it takes quite a bit of getting to grips withs.

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Re: The Distributed Arctic Sea Ice Model
« Reply #45 on: April 13, 2013, 12:49:30 AM »
I do applications and databases, I don't know a lot about the sorts of calculations that would be involved in modelling - never had the need/opportunity to date to get into that sort of thing. I assume they lend themselves very well to parallelism?

Not sure about ice models. For weather/climate, while the same calculations are performed for all cells including adjacent ones, the problem is access to information from adjacent cells. A large cache helps. While GPU can do lots of calcs in parallel, can you get the information there in a timely fashion?


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You just need the platform - and the program.

BOINC is a open source platform used by many distributed computing projects including Seti, CPDN and many more. I think it takes quite a bit of getting to grips withs.
Within the local computing environment I would be very surprised if getting data in or out of the GPU was a bottleneck for the sort of distributed computing we're talking about (data has to move fast to support the graphical requirements of recent generation games - which indeed is why the GPU is quite so chunky in the first place).

Communication between peers over the internet (via TCP-IP, one presumes) would be a much larger issue though (or even over a LAN). Bandwidth constraints and communications latency/reliability orders of magnitude worse than within the local computing environment.

If I got the gist of the BBC project correctly, each distributed platform ran it's own model to completion and the results were aggregated after the fact (SETI has no requirement for communication between peers at all - the ideal parallel processing situation). The only ways I can see to get timely access to information from local cells is if either of the following apply:
  • there is a much larger body of calculations and single threaded time required in between needing information from neighbouring cells
  • the local cells are also calculated and contained within the local environment

Perhaps one could overlap larger blocks of cells between machines, on the assumption that as distance from a neighbour increases the effect diminishes. You'd need to then have some process to reconcile the rapidly increasing differences in the bigger picture though (because a small effect is not no effect - butterfly and wings and all). I think really it would depend upon the model and how it was constructed.

I imagine any proper platform for doing this sort of thing would take some getting to grips with - but arguably at lower cost and barrier to entry than having ones own supercomputer (or maybe even building your own out of a local network - though that might be within the grasp of many larger academic institutions with thousands of machines sitting around anyway). That's before you consider parallel processing (especially of interdependent processes as being discussed here) comes with it's own special set of decidedly non trivial headaches - even in smaller applications.

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Re: The Distributed Arctic Sea Ice Model
« Reply #46 on: April 13, 2013, 01:19:37 AM »
ccgwebmaster, I think, I'm approaching the problem from a different angle. The resource which is available at no cost and en mass are machines. What we don't have are developers. So, I simply look which language do most devs speak. The probability to get some one with JS skills involved is a hell of lot higher than someone who can code shaders on a GPU. And it is much easier to make a running program fast than a fast one running.

Mozilla launched asm.js, google that. They use a special semantic to tell the compiler about types and achieve already 50% with the first implementation, but as said, I wouldn't care about speed now.

Obviously the needed resources are not available here in this forum. Who might be addressed as sponsor? Google Summer of Code comes to my mind. Might be enough to get a very little pilot, let's say version 0.00001 where others can connect later.

Btw. the Navier Stokes code I've linked is part of Google Chrome's test suite. There might be already some one working on a similar project.

Yes, the BBC projects introduces ensembles, that's why each client runs his own (really) simple model. Don't think this approach allows to include ice sheet models or runs on smart phones.

May be you have heard of Internet Census 2012: http://internetcensus2012.bitbucket.org/paper.html One Person did the whole thing, build a plattform, the database and the clients. He scanned the complete Internet, every single IP address, multiple times, by using an interesting distributed approach. Basically he hijacked hundreds of thousands routers and other devices, uploaded silently his own code and let them scan a subnet and report the results.

The project was completely illegal, but he has programmed kind of agents, clever enough to adapt to the machine they run on and to copy itself to other clients - if available - with a subtask to fulfill and to report up stream. Essentially a self replicating avalanche. Very smart.

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Re: The Distributed Arctic Sea Ice Model
« Reply #47 on: April 13, 2013, 08:01:16 AM »
ccgwebmaster, I think, I'm approaching the problem from a different angle. The resource which is available at no cost and en mass are machines. What we don't have are developers. So, I simply look which language do most devs speak. The probability to get some one with JS skills involved is a hell of lot higher than someone who can code shaders on a GPU. And it is much easier to make a running program fast than a fast one running.
If you want proper developers - I question javascript is the place to look! (notwithstanding that some people do some pretty impressive things with it). In my experience most people I've known who use it do exactly what I do with it - use it for it's little niche (client side execution on web pages) and that's about it.

Not all developers are equal - just because someone can string a little code together in javascript certainly doesn't guarantee they have the same abilities as someone who can use much richer and more powerful platforms. I grant that there may not be so many people who can comfortably work with GPUs and design and implement complex (especially involving parallel processing) solutions - but unless I'm mistaken you'd need a little more development experience than a little javascript to tackle meaningful modelling? Any developer capable of doing it with javascript will also be capable of doing it using a whole range of other platforms - because a skilled developer is not typically tied to a particular language or technology (and since javascript is a client side technology you'd still need something else at the server).

If all you can get is someone who can string javascript together, I suspect you're going to be seriously limiting the solutions that can be constructed.
Quote
Mozilla launched asm.js, google that. They use a special semantic to tell the compiler about types and achieve already 50% with the first implementation, but as said, I wouldn't care about speed now.

Obviously the needed resources are not available here in this forum. Who might be addressed as sponsor? Google Summer of Code comes to my mind. Might be enough to get a very little pilot, let's say version 0.00001 where others can connect later.
One could try an open source approach with enthusiasts who enjoy development and who aren't time saturated on other things? No ideas otherwise.

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The project was completely illegal, but he has programmed kind of agents, clever enough to adapt to the machine they run on and to copy itself to other clients - if available - with a subtask to fulfill and to report up stream. Essentially a self replicating avalanche. Very smart.
Otherwise called a worm? A botnet builders ideal? Not so smart when they run out of control and cripple networks.

A little out of my area, but reminds me a bit of metasploit if you configured it to scan a range - and automatically exploit anything it found? If you then automatically installed something to keep propagating the effect?

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Re: The Distributed Arctic Sea Ice Model
« Reply #48 on: April 13, 2013, 11:18:48 AM »
If all you can get is someone who can string javascript together, I suspect you're going to be seriously limiting the solutions that can be constructed.
Things have changed in the last 10 years, you might want to update yourself. This is a good starting point: https://github.com/kripken/emscripten/wiki

Jim Hunt

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Re: The Distributed Arctic Sea Ice Model
« Reply #49 on: April 13, 2013, 10:19:16 PM »
Apologies for my recent absence from the discussion, which I see has been proceeding apace of late. I've been AWOL endeavouring to "make connections" of a different kind.



I would (modestly!) go so far as to describe myself as a "real developer", having been developing software for over 40 years, with the last 30 or so of those concentrating mostly on the "embedded" variety.

My instincts might be a bit old fashioned, but they still tell me that "scripting" languages of whatever flavour won't be up to this sort of job. Java maybe, but not Javascript. I'd be delighted to be proved wrong however!

Using otherwise idle GPU cycles running something in the background more finely divided than BOINC, (and voluntarily donated!) was my original thought. Power consumption would likely skyrocket though, if the concept could be made to work.

Regarding any potential open source project, don't forget about the Google Code placeholder.

Regarding potential sponsors I've previously mentioned the likes of Google, Microsoft, Amazon and Lego. However I've neglected to mention possibly the most obvious. Who is it that keeps going on about a "Smarter Planet"? Who owns Java these days for that matter?

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