[Numpy-discussion] Numpy/Scipy for EC2

David Goldsmith d.l.goldsmith@gmail....
Fri Nov 20 02:47:26 CST 2009

On Thu, Nov 19, 2009 at 5:45 PM, Dan Yamins <dyamins@gmail.com> wrote:

> Hi all:
> I'm just writing to report on my experience using Starcluster, which
> enables the use of NumPy and Scipy in the Amazon EC2 cloud computing
> environment.  The purpose of my email is to extol Starcluster's qualities,
> and suggest that the NumPy community be aware of its development.    I
> suspect there are others in the community who find cloud computing an
> attractive idea but a little daunting to get into,

Thanks, Dan, this is me (for one), and I appreciate you making the time and
effort to do this.  If enough of us dive into this, perhaps we could/should
start a numpig...


> and would be pleasantly surprised out how easy Starcluster makes it to get
> started using NumPy on Amazon EC2.
> For those of you who aren't familiar with AMIs and the Amazon EC2 service,
> see e.g. http://en.wikipedia.org/wiki/Amazon_Elastic_Compute_Cloud.
> Three of the basic concepts are  "Amazon Machine Images" (AMIs),  "machine
> instances" of AMIs, and the Elastic Block Storage (EBS) service.   AMIs are
> disk images containing a virtual machine, including an operating system and
> other software you add on.  Instances are temporarily allocated computers,
> booted with your chosen virtual machine, that you start up on demand, use
> for computations with software from the AMI, and then terminate.   EBS is a
> persistent storage service, also from Amazon, that serves as permanent
> file-systems in the cloud.   You allocate an EBS volume of a given size,
> attach the EBS volume(s) to a running machine instance just like any other
> hard-drive, and use it to store the files  you use/create during
> computation, both during the computation and then for later use whenever you
> start up a new instance.
> A couple of weeks ago I wrote to this list asking for advice on finding a
> good Amazon Machine Instance (AMI) for using NumPy and Scipy on Amazon
> cloud.   I didn't want to have to build a linux machine image with optimized
> blas and lapack myself, and I figured that there might be good existing
> publicly-available AMIs that I could use as a base.   Robert Kern suggested
> that I look into the Starcluster project (
> http://web.mit.edu/stardev/cluster/).
> I have found Starcluster extremely useful.  It made it possible for me to,
> in the course of one day, go from knowing essentially nothing about cloud
> something, to being able to run large-scale parallel clusters with my
> favorite NumPy/SciPy-scripts.
> The basis of what Starcluster offers are two solidly-build AMIs.  The
> operating system is Ubuntu Jaunty, and comes with prebuilt optimized blas
> and lapack, numpy, Scipy, matplotlib, ipython, and several other useful
> packages for scientific computing in python.   It uses Python 2.6, and comes
> in both 32-bit and 64-bit flavors.  The AMIs are based on AMIs from Alestic
> (http://alestic.com/), and are built with best-practices for ensuring
> stability and good interaction with Amazon's system.    They have proved
> very stable and extensible.
> In addition to these AMIs, Starcluster has three extremely useful features:
>     -- Built-in support for mounting EBS drives as NFS filesystems**, and
> then administering the shared drive across multiple machine instances.
>     -- The Sun Grid Engine (SGE), a queuing system for scheduling jobs to
> be run in parallel across instances
>     -- A python module with a few commands that give you an incredibly
> simple interface for automating the process of starting/terminating a
> cluster of instances, mounting the shared drive, starting the grid engine,
> &c -- and configuring your cluster needs (e.g. how many nodes it will
> contain, which AMIs to use, which EBS volumes to mount etc.).
> As a result, all you have to do to have a NumPy-enabled cluster-on-demand
> is:
>     1) Get an amazon EC2 account, and the accompanying security credentials
> (.501 certificates and PGP keypair) for your account.
>     2) Install starcluster ("easy_install starcluster")
>     3) Follow the installation procedure on the starcluster website for
> getting, attaching, and formatting an EBS volume as an NFS drive.
>     4) Set up your starcluster configuration file.
>     5) Start a 1-node cluster, modify the installation as you see fit, and
> re-bundle the result into a new AMI as described on the Amazon website
> http://docs.amazonwebservices.com/AWSEC2/latest/GettingStartedGuide/.
> (Don't forget to edit your starcluster configuration file to reflect your
> new AMI.)   This step is optional -- If you don't need anything else
> special, you can just use Starcluster's base images.
> After that, starting a cluster is as easy as typing single command
> ("starcluster -s").  To submit parallel jobs on your cluster, you can learn
> to use the Sun Grid Engine "qsub" command (
> http://gridengine.sunsource.net/nonav/source/browse/~checkout~/gridengine/doc/htmlman/htmlman1/qsub.html<http://gridengine.sunsource.net/nonav/source/browse/%7Echeckout%7E/gridengine/doc/htmlman/htmlman1/qsub.html>)
> or use the python bindings to the SGE interface (
> http://code.google.com/p/drmaa-python/).     Or, if you like Parallel
> Python, that works perfectly well on these clusters too.
> Overall, in my experience, Starcluster has been easy, stable and powerful,
> and I encourage anyone who is curious about cloud computing with Numpy to
> look into it.
> Starcluster is by no means a finished project.  At the moment, you can only
> administer one cluster at a time from your given local machine, since
> starcluster has no notion of a "session" and it can't distinguish between
> different clusters you've started up (you can *start* multiple clusters,
> but then any starcluster commands that you type in your local terminal might
> get confused about which amazon machine instances you're referring to, so it
> has trouble administering them.)    Also, there's no dynamic load balancing,
> so once you've started a cluster with a certain number of nodes, you're
> stuck with that number of computers while the cluster is running, even if
> you're only using a few of them or suddenly need more.
> The developer of the project (*Justin Riley)* says on his website that
> he's planning to add these features in the next release.    Now, I'm not the
> creator or developer or maintainer of Starcluster, and I have no affiliation
> with Justin Riley or the project whatsoever, so I want to make it clear I
> don't speak for them in any way except as a satisfied user.  I don't know
> what his commitment to his development plans are, either -- however, I hope
> he sticks to his timeline, as I think continuing the vigorous development of
> his project would be a real plus for the NumPy community.  I'm hoping that
> if others in the NumPy community like his project and start using it, that
> will make add to the likelihood of continued development. (If anyone from
> the NumPy community is interesting in helping the developer out, perhaps you
> should consider shooting him an email.)
> Anyhow, I apologize for this long email, and hope it may be of use to
> somebody!
> Dan
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