[Beowulf] Java vs C++ for interfacing to parallel library

Jonathan Ennis-King Jonathan.Ennis-King at csiro.au
Sun Aug 20 21:02:43 EDT 2006


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To give additional context, the choice of language is partly driven by
the desire to make the code open source (eventually) and usable by other
scientists (who are not exclusively programmers). This consideration
rules out the arcane or new-fangled. My impression is that the only
languages with wide community support for numerical scientific computing
are Fortran (F77 or F90), C, C++ and Java (e.g. look at the order of
appearance of the Numerical Recipes books - although they did have Pascal).

Until recently I would have left Java out of that list, since I assumed
that the performance penalty would be too large. However one of my
colleagues has recently completed a large open source seismic inversion
code in Java, which works well enough. I've also been influenced by this
article by David Hale
www.mines.edu/~dhale/papers/Hale06JavaAndCppPlatformsForScientificComputing.pdf
comparing C++ and Java for scientific computing.

Obviously there must be a computational cost to OO abstraction, but you
might be willing to tolerate that cost if it was say 10-20% relative to
C. I'm told that Java has improved quite a lot in this domain over time.
One also finds cases in which the differences between compilers for the
same language can as large as the difference between languages. Java
seems to have advantages in ease and speed of development, especially in
memory management, and good standard cross-platform libraries e.g. for
graphics and UI.

One way to alleviate the performance hit is of course to use a 90% Java
strategy, where the computationally intensive 10% (here, parallel sparse
matrix inversion) is handled in C.
It's the mixed language part that worries me with Java, especially in
the light of rgb's comments. It is claimed by some that Java and C++ are
largely incompatible. Or is this all solved in the Java native interface
(JNI)?

My specific question was whether anyone out there was running parallel
codes either written completely in Java, or with Java wrappering some
big numerical library for the hard part. Are there any additional issues
 with parallel performance, or it this just a subcase of Java-C
interfacing in a scalar setting.


The other option is the Unix-like strategy suggested by rgb, where for
example the computational part is completely written in C, and then the
pre and post-processing which benefit from a GUI are written in some
other language (e.g. Java), or strung together from other unix tools and
wrapper languages.


Robert G. Brown wrote:
> On Sun, 20 Aug 2006, Joe Landman wrote:
> 
>> Jonathan:
>>
>> Jonathan Ennis-King wrote:
>>
>>> Does anyone have experience writing parallel Java code (using MPI) with
>>> calls to C libraries which also use MPI? Is this possible/sensible? Is
>>> there a big performance hit relative to doing the same in C++?
>>
>>
>> Unless all of the important optimizable calculation is done in libraries
>> that you are stitching together with Java glue, the compiled languages
>> are likely to be quite a bit faster.
>>
>> There is a sizeable abstraction penalty associated with OO languages.
>> Many of the design patterns that they encourage (object factories,
>> inheritance chains, etc) are anathema to high performance.
> 
> 
> Hear, hear!
> 
>>> I'm considering writing some parallel code to do fluid flow in porous
>>> media, the heart of which is solving systems of sparse linear equations.
>>> There are some good libraries in C which provide the parallel solver
>>> (e.g. PETSC), but I'm trying to resolve which language to use for my
>>> code. The choice is between C++ and Java, and although I'm favouring
>>> Java at present, I'm not sure about its performance in this context.
>>
>>
>> Hmmm.  For this, C or Fortran may be far more appropriate.  Depends upon
>> what it is you want to do with the code.  High performance using MPI
>> depends upon many factors.  If there is one particular part of the code
>> that is better served by an OO based language, then I might suggest
>> designing/implementing all the speed sensitive bits in a language which
>> lets you achieve high performance, and then interfacing them to your OO
>> language so that the OO system isn't being used for the critical time
>> sensitive portions.
> 
> 
> <disclaimer>Parts of the stuff below are editorial comment and religious
> belief and can be ignored or sniffed at by those of differing
> belief.</disclaimer>
> 
> Remember well the observation that you can write object oriented code in
> a procedural language (and ditto, you can write procedural code in an OO
> language).  Matching the language to the kind of code -- or more
> likely, the personal taste of the coder -- simply makes development a
> bit more simple and natural.
> 
> Untimately, OO vs procedural code is a matter of style as much as
> anything else.  I write "real" code exclusively in C.  I'm in the
> process of (re)writing a random number testing program (dieharder) into
> a library-based tool that was originally (first pass) quite procedural
> in its design.  In the second pass, as I came to fully understand the
> data objects better in practice and could start to see how the code
> could be simplified and compressed, I began to introduce a set of "lazy"
> shared objects for certain parts of the code.
> 
> In the third (current) pass I'm splitting off all of the actual testing
> code, as opposed to the startup/results/presentation UI code, into a
> library.  Since most of the tests share a very similar implementation
> structure and certain control variables in common, I can now see
> precisely how to make the code very object oriented with a set of "test
> objects" (structs and similarly structured test implementations that
> read from them and fill them in) and a single set of "shell" code for
> calling a standard test.  This reduces writing a UI to nothing but
> simple, repetitive boilerplate for calling the actual tests and
> displaying the returned results -- one can focus on the human side of
> the UI and stop worrying about the tests, and one can relatively easily
> and scalably add more tests or RNGs to test.
> 
> Since the code is still both lazy OO and C, I can freely intersperse the
> use of pointers, can choose to treat variables (incluing all
> structs/objects) as "opaque" or not as makes sense in the code, and keep
> the code as efficient as C can make it, which is to say damn near as
> efficient as assembler.  The "objectness" of the encapsulated tests just
> permits me to write a relatively clean API to the library (without too
> many test specific global/shared variables or the even greater hassle of
> dealing with passing variable length argument lists through layers of
> encapsulating subroutines) so that when I'm done adding a UI or GUI or
> implementing the tests native inside e.g.  R or octave or whatever will
> be fairly straightforward.
> 
> The point being that one CAN write non-lazy OO code in C or even in
> Fortran -- that's more a question of program design and an understanding
> of the basic data objects that a program requires, although it certainly
> helps if the language permits the definition of a struct of one sort or
> another.  One has the choice in C, though, of writing fully OO, lazy
> (mixed) OO or fully procedural code when and where that is appropriate
> for either ease of coding or program efficiency.  I suppose that choice
> exists to some extent for at least some non-fascist OO environments
> (e.g. C++ as a sort-of superset of C) but I think that the only people
> who even know how to do so are those who have learned to code in a
> non-OO language first -- people who learn C++ as their primary language
> tend to be pretty clueless about pointers or the performance advantages
> of NOT using protection and inheritance in your structs but just letting
> everything access them directly.  C provides few safety nets but rather
> permits you to do pretty much anything you like, at your own risk, in
> code that is ultimately transparent.
> 
> Now, I personally believe that all nontrivial programs go through stages
> like the three described above no matter what language they are written
> in.  This is one of the reasons that Wirth's Pascal had its day and that
> it passed -- whether one starts at the top or at the bottom or both, one
> is likely to encounter mismatches that require rethinking all or part of
> the memory hierarchy one begins with in any difficult project.  In that
> SECOND pass and beyond, both strict-topdown and strict-bottomup
> languages tend to require MORE work to fix than one that is less
> hierarchically prestructured.
> 
> Perhaps there are OO ubercoders that can just "see" what the data
> objects appropriate to a complex application are from the beginning and
> can start off with the right top level, mid, AND bottom level objects
> all perfectly enmeshed and integrated but I have yet to meet one.  One
> of the great (IMO) illusions promoted by OO fanatics is that by using an
> OO language (per se) to write the code in the first place one can
> somehow shorten this process and home in on the correct hierarchy of
> data structures (objects or not) that optimally support the
> application's efficient implementation from top to bottom.  This is not
> my experience, but hey, the world is a big place and there may be people
> who just think that way and for them it may be true.
> 
> For code like the specific stuff you want to implement above that have
> efficient libraries written in C, my guess is that you would do best
> using C -- this is pretty much a no-brainer.  It is highly probable that
> in C you have the best access to example programs using the library,
> UIs, human support in the form of others who use the libraries in their
> C code, and more.  Even communicating with the author/maintainers of the
> library is bound to be simplest if you are implementing in C.  Second
> best would almost certainly be C++, as C++ can (I believe) call C
> libraries fairly transparently or with a minimal C++ encapsulation of
> the C prototypes and data structures.
> 
> OTOH Fortran and C tend to have somewhat different subroutine call
> mechanisms so binding a C library into fortran code or VV tends to be a
> PITA -- for example, C always passes subroutine arguments by value,
> fortran by reference.  In addition, C and fortran use slightly different
> conventions for other simple stuff e.g. terminating a string.  Some of
> the issues associated with the port are mentioned here:
> http://star-www.rl.ac.uk/star/dvi/sun209.htx/node4.html as well as
> elsewhere on the web.  Basically, calling C libraries in fortran code is
> possible but requires some work and code encapsulation (and vice versa
> for calling fortran routines from inside C code, IIRC -- fortran/C
> compiler folks can check me on this:-).
> 
> Java, octave, matlab, python, perl etc. are MUCH WORSE in this regard.
> All require NONTRIVIAL encapsulation of the library into the interactive
> environment.  I have never done an actual encapsulation into any of
> them, but I'll wager that it is really quite difficult because each of
> them has their very own internal data types that are REALLY opaque
> objects that bear little overt resemblance to the simple "all data
> objects can be viewed as a projection onto a block of memory with either
> typed or pointer driven offset arithmetic" view of data in C or for that
> matter C++ or Fortran (with slighly different projective views in both
> cases).
> 
> These languages typically permit you to allocate memory by just using a
> named variable.  This is marvelously convenient for an interactive
> environment -- it is marvelously expensive in terms of program
> efficiency because the underlying environment has to manage allocating
> the memory transparently extensibly (most of the languages permit you to
> allocate whole vectors or matrices of variables by just referencing
> them), tracking instances of the memory in code, and freeing the memory
> when it is no longer referenced or being used.  Conservatively, so that
> they tend to keep things if there is ANY CHANCE of their ever being
> referenced, making them typically memory hogs almost as bad as a C
> program would be if every memory reference in the program was to static
> global memory -- no memory allocation or freeing at all, beyond whatever
> goes on stack/heap in the course of subroutine calls or internal
> function execution.  Complicated hashes or advanced list structures are
> used to keep the execution itself moderately efficient (but highly
> INefficient compared to a decent compiler with flat memory outlays).
> 
> The point being that you have to interface these opaque and not
> obviously documented data types to the C library calls.  This is surely
> possible -- it is how all those perl libraries, matlab toolboxes, java
> interfaces come about.  It will probably require that you learn WAY more
> about how the language itself is implemented at the source level than
> you are likely to want to know, and it is probably not going to be
> terribly easy...
> 
>    rgb
> 
>>
>>>
>>>
>>>   Jonathan Ennis-King
>>>
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>>
> 


- --
  Jonathan Ennis-King
  email: Jonathan.Ennis-King at csiro.au
  post: CSIRO Petroleum, Private Bag 10, Clayton South, Victoria, 3169,
Australia
  ph: +61-3-9545 8355 fax: +61-3-9545 8380

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