Sorry, but not of this is making sense to me. We had a long discussion
about how the library doesn't test for large scale problem
performance. A lot of algorithms probably do not scale well as the
result. There was talk of dropping sparse support in linear algebra.
So instead of fixing that, you jump to parallelization, which is
needed only for large scale problems, which this library does not
handle well even in single thread right now.
The most significant impact you can have is fixing the linear algebra
component.
On Feb 7, 2013, at 5:06 PM, Gilles <gil...@harfang.homelinux.org> wrote:
> On Thu, 07 Feb 2013 08:32:46 -0800, Phil Steitz wrote:
>> On 2/7/13 8:04 AM, Gilles wrote:
>>> On Thu, 07 Feb 2013 07:01:42 -0800, Phil Steitz wrote:
>>>> On 2/7/13 4:58 AM, Gilles wrote:
>>>>> On Wed, 06 Feb 2013 09:46:55 -0800, Phil Steitz wrote:
>>>>>> On 2/6/13 9:03 AM, Gilles wrote:
>>>>>>> On Wed, 06 Feb 2013 07:19:47 -0800, Phil Steitz wrote:
>>>>>>>> On 2/5/13 6:08 AM, Gilles wrote:
>>>>>>>>> Hi.
>>>>>>>>>
>>>>>>>>> In the thread about "static import", Stephen noted that
>>>>>>>>> decisions
>>>>>>>>> on a
>>>>>>>>> component's evolution are dependent on whether the future of
>>>>>>>>> the
>>>>>>>>> Java
>>>>>>>>> language is taken into account, or not.
>>>>>>>>> A question on the same theme also arose after the
>>>>>>>>> presentation of
>>>>>>>>> Commons
>>>>>>>>> Math in FOSDEM 2013.
>>>>>>>>>
>>>>>>>>> If we assume that efficiency is among the important
>>>>>>>>> qualities for
>>>>>>>>> Commons
>>>>>>>>> Math, the future is to allow usage of the tools provided by the
>>>>>>>>> standard
>>>>>>>>> Java library in order to ease the development of multi-threaded
>>>>>>>>> algorithms.
>>>>>>>>>
>>>>>>>>> Maintaining Java 1.5 source compatibility for the reason
>>>>>>>>> that we
>>>>>>>>> may need
>>>>>>>>> to support legacy applications will turn out to be
>>>>>>>>> self-defeating:
>>>>>>>>> 1. New users will not consider Commons Math's features that are
>>>>>>>>> notably
>>>>>>>>> apt to parallel processing.
>>>>>>>>> 2. Current users might at some point simply switch to another
>>>>>>>>> library if
>>>>>>>>> it proves more efficient (because it actually uses
>>>>>>>>> multi-threading).
>>>>>>>>> 3. New Java developers will be turned away because they will
>>>>>>>>> want
>>>>>>>>> to use
>>>>>>>>> the more convenient features of the language in order to
>>>>>>>>> provide
>>>>>>>>> potential contributions.
>>>>>>>>>
>>>>>>>>> If maintaining 1.5 source compatibility is kept as a
>>>>>>>>> requirement, the
>>>>>>>>> consequence is that Commons Math will _become_ a legacy
>>>>>>>>> library.
>>>>>>>>> In that perspective, implementing/improving algorithms for
>>>>>>>>> which a
>>>>>>>>> parallel version is known to be more efficient is plainly a
>>>>>>>>> waste of
>>>>>>>>> development and maintenance time.
>>>>>>>>>
>>>>>>>>> In order to mitigate the risks (both of upgrading and of not
>>>>>>>>> upgrading
>>>>>>>>> the source compatibility requirement), I would propose to
>>>>>>>>> create a
>>>>>>>>> new
>>>>>>>>> project (say, "Commons Math MT") where we could implement new
>>>>>>>>> features[1]
>>>>>>>>> without being encumbered with the 1.5 requirement.[2]
>>>>>>>>> The "Commons Math MT" would depend on "Commons Math" where we
>>>>>>>>> would
>>>>>>>>> continue developing single-thread (and thread-safe) "tasks",
>>>>>>>>> i.e.
>>>>>>>>> independent units of processing that could be used in
>>>>>>>>> algorithms
>>>>>>>>> located in "Commons Math MT".
>>>>>>>>>
>>>>>>>>> In summary:
>>>>>>>>> - Commons Math (as usual):
>>>>>>>>> * single-thread (sequential) algorithms,
>>>>>>>>> * (pure) Java 5,
>>>>>>>>> * no dependencies.
>>>>>>>>> - Commons Math MT:
>>>>>>>>> * multi-thread (parallel) algorithms,
>>>>>>>>> * Java 7 and beyond,
>>>>>>>>> * JNI allowed,
>>>>>>>>> * dependencies allowed (jCuda).
>>>>>>>>>
>>>>>>>>> What do you think?
>>>>>>>>
>>>>>>>> There are several other possibilities to consider:
>>>>>>>>
>>>>>>>> 0) Implement multithreading using JDK 1.5 primitives
>>>>>>>> 1) Set things up within [math] to support parallel execution in
>>>>>>>> JDK
>>>>>>>> 1.7, Hadoop or other frameworks
>>>>>>>> 2) Instead of a new project, start a 4.x branch targeting JDK
>>>>>>>> 1.7
>>>>>>>>
>>>>>>>> I think we should maintain a version that has no dependencies
>>>>>>>> and no
>>>>>>>> JNI in any case.
>>>>>>>>
>>>>>>>> Starting a branch and getting concrete about how to parallelize
>>>>>>>> some
>>>>>>>> algorithms would be a good way to start. One thing I have not
>>>>>>>> really investigated and would be interested in details on is
>>>>>>>> what
>>>>>>>> you actually get in efficiency gain (or loss?) using fork /
>>>>>>>> join vs
>>>>>>>> just using 1.5+ concurrency for the kinds of problems we
>>>>>>>> would end
>>>>>>>> up using this stuff for.
>>>>>>>>
>>>>>>>> Thinking about specific parallelization problem instances would
>>>>>>>> also
>>>>>>>> help decide whether 1) makes sense (i.e., whether it makes
>>>>>>>> sense as
>>>>>>>> you mention above to maintain a single-threaded library that
>>>>>>>> provides task execution for a multithreaded version or
>>>>>>>> multithreaded
>>>>>>>> frameworks).
>>>>>>>>
>>>>>>>> One more thing to consider is that for at least some users of
>>>>>>>> [math], having the library internally spawn threads and/or peg
>>>>>>>> multiple processors may not be desirable. It is a little
>>>>>>>> misleading
>>>>>>>> to say that multithreading is the way to get "efficiency."
>>>>>>>> It is
>>>>>>>> really the way to *use* more compute resources and unless there
>>>>>>>> are
>>>>>>>> real algorithmic improvements, the overall efficiency may
>>>>>>>> actually
>>>>>>>> be less, due to task coordination overhead. What you get is
>>>>>>>> faster
>>>>>>>> execution due to more greedy utilization of available cores.
>>>>>>>> Actual
>>>>>>>> efficiency (how much overall compute resource it takes to
>>>>>>>> complete a
>>>>>>>> job) partly depends on how efficiently the coordination
>>>>>>>> itself is
>>>>>>>> done (which JDK 1.7 claims to do very well - I have just not
>>>>>>>> seen
>>>>>>>> substantiation or any benchmarks demonstrating this) and how the
>>>>>>>> parallelization effects overall compute requirements. In any
>>>>>>>> case,
>>>>>>>> for environments where library thread-spawning is not
>>>>>>>> desirable, I
>>>>>>>> think we should maintain a single-threaded version.
>>>>>>>
>>>>>>> Unless I missed the point, those reasons are exactly why I
>>>>>>> propose to
>>>>>>> have 2 projects/components. One, "Commons-Math", does not fiddle
>>>>>>> with
>>>>>>> resources, while the other would provide a "parallelizationLevel"
>>>>>>> setting for the algorithms written to possibly take advantage of
>>>>>>> the
>>>>>>> Java 5+ "task framework".
>>>>>>
>>>>>> OK, what about the 4.x option?
>>>>>>>
>>>>>>> Yes, we could still be good by using only Java 5's concurrency
>>>>>>> features
>>>>>>> but the issue I raise is not only about concurrency but about
>>>>>>> evolution/progress/maintenance, all things that require raising
>>>>>>> interest
>>>>>>> from new contributors (unless it's fine that Commons Math be
>>>>>>> tagged as a
>>>>>>> "library of the past"...).
>>>>>>
>>>>>> +1 for experimenting with parallelization. I would just like to
>>>>>> understand if the JDK 7 stuff really adds much - in particular,
>>>>>> does
>>>>>> it handle coordination / cpu allocation better than you could
>>>>>> easily
>>>>>> do it with 1.5. More supported JDKs == more potential users, so I
>>>>>> like to see a real reason to bump the JDK level.
>>>>>>>
>>>>>>> But using concurrency features in "Commons Math" would also
>>>>>>> contradict
>>>>>>> your own point ("we should maintain a single-threaded
>>>>>>> version"): I
>>>>>>> agree,
>>>>>>> and that's why I proposed this other project...
>>>>>>>
>>>>>>> As for efficiency (or faster execution, if you want), I don't
>>>>>>> see the
>>>>>>> point in doubting that tasks like global search (e.g. in a
>>>>>>> genetic
>>>>>>> algorithm) will complete in less time when run in parallel...
>>>>>>>
>>>>>>> As I summarized previously, having a "Commons Math MT" would
>>>>>>> bring no
>>>>>>> inconvenience, contrary to either your points 0, 1, or 2. [No
>>>>>>> inconvenience to me, that is, but to people with requirements
>>>>>>> like
>>>>>>> "Java 5 compatible" or "no multi-threading").
>>>>>>> As I indicated, the basic "task" could be defined in "Commons
>>>>>>> Math" and
>>>>>>> "Commons Math MT" would provide the parallelization "glue" (e.g.
>>>>>>> to divide
>>>>>>> the search space of the GA).
>>>>>>
>>>>>> I think it is best at this point to cut a branch and actually
>>>>>> start
>>>>>> working on specific algorithms. Having a set of candidate
>>>>>> algorithms for parallelization will help us decide what we
>>>>>> actually
>>>>>> need and how it might work. I would personally favor the 4.x
>>>>>> approach, with thread-spawning behavior configurable.
>>>>>
>>>>> It seems fair to wait until parallel algorithms are actually
>>>>> implemented.
>>>>>
>>>>> However it is not clear what you mean with "the 4.x approach": if
>>>>> it is
>>>>> actually allowing Java 7, that would mean that, starting from 4.0,
>>>>> we'll
>>>>> indeed drop support of earlier JVMs!
>>>>> Why would this be preferred to having 2 projects? Of course, if
>>>>> everyone
>>>>> agrees to that move to Java 7, that's fine. :-)
>>>>
>>>> What I meant was that instead of creating a new component, we would
>>>> just create a new release line. Like what tomcat does for servlet
>>>> spec versions. I guess this does mean that we end up having to
>>>> stabilize the 3.x APIs because no additional "major" release would
>>>> be allowed in that line. That would be a *good thing* IMO as long
>>>> as we can do it cleanly. If not, maybe we end up having to use 5.x
>>>> for the JDK 1.7+ version, using 4.0 to get to a stable API for the
>>>> current trunk code.
>>>
>>> There's a still the human resource problem: we don't have it to
>>> maintain
>>> a single branch; having two will only make it worse.
>>
>> Yes, but the "new project" approach has the same problem.
>
> Yes.
> However, I meant it as a way to separate concerns, as shown
> by diverging opinions, even in the few people who take part
> in this discussion or in previous ones about the same subject.
>
> A sibling (not separate!) project could allow interested
> people to experiment while not adding yet another "distraction"
> to the main project, where people more focused on the
> mathematical (for lack of a better word) side can continue
> their own improvements.
> A healthy interaction could even come out of having a "public"
> use-case in the form of a project that needs certain facilities
> (algorithms as tasks) in order to provide multi-thread
> utilities to users (who might prefer not to have to implement
> them themselves at a higher level).
>
>>>>> On the other hand, if we keep Java 5, at least until we get use
>>>>> cases or
>>>>> contributions that would benefit from features in JDKs newer than
>>>>> 1.5,
>>>>> there is no need to create a branch; we can just go on with adding
>>>>> multi-thread codes to the trunk (to become part[1] of the upcoming
>>>>> 3.x
>>>>> releases).
>>>>
>>>> That is why I wanted to get a feel for what the JDK 1.7 stuff really
>>>> buys you. Has anyone seen benchmarks showing better performance
>>>> using 1.7 than can be obtained just using 1.5 concurrency
>>>> primitives?
>>>
>>> Again, there are separate issues:
>>> 1. Coding in Java 7
>>> 2. Running with the JVM shipped with JDK 1.7
>>>
>>> The newer JVMs are faster, independently of whether new features
>>> of the
>>> language are used.
>>> But it could well be that some of the new features allow even better
>>> performance (as is foreseen for Java 8).
>>
>> Agreed. I am interested in understanding better both how much
>> easier it actually is to code and whether the 1.7 framework
>> materially improves scheduling / allocation over what you could do
>> just using 1.5 primitives.
>
> I cannot provide proof, but nor is anyone on this list
> eager to prove the contrary; hence the proposal to set
> up a "playground".
>
>>>> Has anyone used 1.7 to parallelize numerical algorithms
>>>> and found it really easier / more performant?
>>>
>>> Where are those people who could answer?
>>
>> This is a public list :)
>>> That is one of the points I raised. If we maintain source
>>> compatibility
>>> with a language version that is 9 years old, not many contributors
>>> are
>>> going to be interested. Thus reducing the chance to get answers...
>>>
>>>> Any opinions /
>>>> responses to Konstantin's comment on where parallelization should be
>>>> implemented - i.e. in the library vs somewhere up the stack?
>>>
>>> What was the _question_? ...
>>
>> The question he implicitly raised was whether or not it makes sense
>> for a low-level library to parallelize tasks / run across cores.
>
> In several areas, CM is not a low-level library (GA, multi-start
> optimizers for example). In other areas like FFT, a user can
> legitimately expect top performance without having to handle
> parallelization by himself.
>
>> This is a legitimate question. It may be better actually to set
>> things up so that higher-level frameworks or applications can
>> arrange parallel execution rather than embedding it in the low-level
>> library itself. This is also what I was referring to when I said
>> that in some contexts, thread-spawning / cpu hogging may not be
>> desirable.
>
> For several cases (GA, FFT, multi-start optimizers), I have the
> opposite viewpoint: multi-threading is a implementation detail,
> that could be handled at a _lower_ level. Of course, the user can
> decide whether to enable more than one thread.
>
>>>> Any
>>>> ideas how to set things up so that [math] code can play nicely with
>>>> concurrency frameworks?
>>>
>>> That's a strange question in the context of a project that tries hard
>>> not to have any dependency.
>>
>> I did not mean necessarily to bring in dependencies; but rather to
>> make it easy for computational tasks executed by [math] code to be
>> managed by external concurrency frameworks, e.g. Hadoop.
>
> In the context of Commons Math, we often heard that "no dependency"
> is good. Then, it is also good to not impose _implicit_ dependencies
> (like: "If you use Hadoop, you could have better performance"). In a
> way, the CM development "model" is: "We provide a toolkit of efficient
> procedures, and you, the user, get top performance (on a best effort
> basis of course)."
> If we can provide better performance through multi-threading, why not?
> Nobody will be forced to use it: they will use the "basic" (sequential)
> tasks, or set the "parallelizationLevel" setting to 1.
>
> Gilles
>
>> Phil
>>> If the requirement is to only depend on the standard JDK: the
>>> framework
>>> is in
>>> java.util.concurrent
>>> and all we need to do is to define "tasks" that can be "submitted to
>>> an executor:
>>>
>>> http://docs.oracle.com/javase/1.5.0/docs/api/java/util/concurrent/AbstractExecutorService.html#submit(java.util.concurrent.Callable)
>>>
>>>
>>> Regards,
>>> Gilles
>
>
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