On 5/4/2011 3:13 AM, Russel Winder wrote:
On Tue, 2011-05-03 at 23:14 -0400, dsimcha wrote:
[ . . . ]
BTW, yes, I know Java and C# can be pretty fast sometimes. The problem
is that they both have abstractions you can't get beneath in your most
performance-critical code. If you're writing code from scratch (as
opposed to something that would benefit from tons of libraries that D
doesn't have yet), I also think they're not as productive because they
don't make metaprogramming easy.
I don't know about C#/CLR (no experience of knowledge) but for
Groovy/Scala/Java/Clojure on the JVM, and indeed Python on the PVM, if
there is a small piece of code that is truly performance critical and
you can't get the JVM/JIT to make it fast enough and native code can
then you call out to C or C++ -- real performance data not speculation
is required here though. Of course this is far, far easier with Python.
Much of the "need flexibility"/"developer time is more important than
run time because I am just using APIs that are already optimized"
HPC-ish stuff is now happening in Python with C/C++/Fortran libraries,
cf. NumPy, SciPy.
True but somewhat irrelevant. The problem with this is that you're
still writing the critical bits in C/C++, and furthermore a dialect of
C/C++ that requires a well-defined ABI. In my experience, when mixing
languages there's always friction along the borders. Furthermore, when
you do something like this you have to specify types explicitly. D and
C++ are the only languages I'm aware of that let you write efficient
generic code. After using D, C++ seems half-assed in this area. D is
the only language I'm aware of that lets you do it **well**.
