Multi-threaded access to shared memory space

I have a pure Ruby project (no Rails) where I would like multiple
“tasks” (ruby processes more or less) to run in parallel (collectively
taking advantage of multiple CPU cores) while accessing a shared memory
space of data structures.

OK, that’s a mouthful.

  • single machine, multiple cores (4 or 8)

  • step one: pre-load a number of arrays and hashes (could be a couple GB
    worth in total) into memory

  • step two: launch several independent Ruby scripts to search and read
    from the data pool in order to aggregate data in new sets to be written
    to text files.

Ruby 1.8’s threading would seem poorly suited to this. Can 1.9 run
multiple threads each accesing the same RAM-space while using all cores
of the machine?

I’ve looked at memcache, but it seems like it could store and retrieve
one of my pool’s arrays, but it cannot look inside that array and
retrieve just a single row of it? It would want to return the whole
array, yes? (not good if that array is 100MB).

– gw

On Jun 29, 2008, at 23:58 PM, Greg W. wrote:

  • step one: pre-load a number of arrays and hashes (could be a
    cores
    of the machine?

At present, 1.9 has a global VM lock, so only one C thread can be
running ruby code at a time.

I’ve looked at memcache, but it seems like it could store and retrieve
one of my pool’s arrays, but it cannot look inside that array and
retrieve just a single row of it? It would want to return the whole
array, yes? (not good if that array is 100MB).

memcache is just a cache and not designed to be used as a persistent
store. It may loose your data if you are not careful.

You’re probably looking for something mmap and several forked
cooperative processes.

On Jun 30, 2008, at 12:58 AM, Greg W. wrote:

  • step one: pre-load a number of arrays and hashes (could be a
    cores
    of the machine?

I’ve looked at memcache, but it seems like it could store and retrieve
one of my pool’s arrays, but it cannot look inside that array and
retrieve just a single row of it? It would want to return the whole
array, yes? (not good if that array is 100MB).

Take a look at mmap

http://raa.ruby-lang.org/project/mmap/

Blessings,
TwP

On 30 Jun 2008, at 07:58, Greg W. wrote:

  • step one: pre-load a number of arrays and hashes (could be a
    cores
    of the machine?

I’ve looked at memcache, but it seems like it could store and retrieve
one of my pool’s arrays, but it cannot look inside that array and
retrieve just a single row of it? It would want to return the whole
array, yes? (not good if that array is 100MB).

If you want to stay in pure Ruby, take a look at DRb and Rinda. Even
if not directly applicable they should give you some inspiration.

Ellie

Eleanor McHugh
Games With Brains
http://slides.games-with-brains.net

raise ArgumentError unless @reality.responds_to? :reason

Greg W. wrote:

Ruby 1.8’s threading would seem poorly suited to this. Can 1.9 run
multiple threads each accesing the same RAM-space while using all cores
of the machine?

No, but JRuby’s threads can.

  • Charlie

On Jun 30, 2008, at 12:58 AM, Greg W. wrote:

  • step one: pre-load a number of arrays and hashes (could be a
    cores

tim is right i think, mmap is a great approach. i’ve used the
following paradigm many times for processing large datasets:

. mmap in the file
. decide the chunk size
. fork n processes working on each chunk

because mmap is carried across the fork you don’t do any data
copying. actually the memory won’t even be paged in until the
children read them.

this is really ideal if the children can write the output - in
otherwords if the children don’t have to return data to the parent
since returning a huge chunk of data can be expensive.

you might easily end up being IO bound and not CPU bound - in the
similar processing i’ve done i’ve often found that the work scales
best with the number of disk controllers, not the number of cpus -
something worth considering

another approach to consider is to put all the input (or pathnames to
it) into an sqlite database and then launch processes to work on it.
this may not seem sexy but it has some huge advantages: namely that
you’ll be able to maintain state across runs which will allow you to
make programming errors but still be making forward progress. this
isn’t glamerous but it’s very powerful as it allows incremental
development and even coordination of ruby with other languages - like c.

one last suggestion if you have a stack of linux machines available

. install rq
. submit a bunch of jobs that process a chunk of data

go home for the day :wink:

with rq you should be able to setup a linux cluster in a few minutes
and just submit a slow ruby script to 10 machines running 4 jobs each
no problem. you could also use rq on an 8 core machine to manage the
jobs for you

food for thought.

ref:

http://www.linuxjournal.com/article/7922
http://codeforpeople.com/lib/ruby/rq/rq-3.1.0/README
(rq 3.4.0 has a bug in it so use 3.1 if you decide to try that route)

a @ http://codeforpeople.com/

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