The GCC manual says:
-fobjc-direct-dispatch
Allow fast jumps to the message dispatcher. On
Darwin this is accomplished via the comm page.
Can I assume this flag eliminates dynamic dispatch? How does it work?
I believe it should be as fast as a C function call if it is linked directly.
No, the dynamic dispatch is still there (calls still route through objc_msgSend). And this option doesn't introduce any difference currently with x86(-64).
From http://developer.apple.com/legacy/mac/library/documentation/DeveloperTools/gcc-3.3/gcc/Objective_002dC-Dialect-Options.html:
For some functions (such as objc_msgSend) called very frequently by Objective-C programs, special entry points exist in high memory that may be jumped to directly (e.g., via the "bla" instruction on the PowerPC) for improved performance. The fobjc-direct-dispatch option will cause such jumps to be generated. This option is only available in conjunction with the NeXT runtime; furthermore, programs built with the -fobjc-direct-dispatch option will only run on Mac OS X 10.4 (Tiger) or later systems.
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I'm working on a very demanding project (actually an interpreter), exclusively written in D, and I'm wondering what type of optimizations would generally be recommended. The project makes heavy use of GC, classes, asssociative arrays, and pretty much anything.
Regarding compilation, I've already experimented both with DMD and LDC flags and LDC with -flto=full -O3 -Os -boundscheck=off seems to be making a difference.
However, as rudimentary as this may sound, I would like you to suggest anything that comes to your mind that could help speed up the performance, related or not to the D language. (I'm sure I'm missing several things).
Compiler flags: I would add -mcpu=native if the program will be running on your machine. Not sure what effect -Os has in addition to -O3.
Profiling has been mentioned in comments. Personally under Linux I have a script which dumps a process's stack trace and I do that a few times to get an idea of where it's getting hung up on.
Not sure what you mean by GS.
Since you mentioned classes: in D, methods are virtual by default; virtual methods add indirections and are not inlineable. Make sure only those methods that must be virtual are. See if you can rewrite your program using a form of polymorphism that doesn't involve indirections, such as using template metaprogramming.
Since you mentioned associative arrays: these make heavy use of the GC; to speed them up, switch to a third-party library that works on top of std.allocator, such as https://github.com/dlang-community/containers
If some parts of your code are parallelizable, std.parallelism is a good tool for this.
Since you mentioned that the project is an interpreter: there are many avenues for optimizing them, up to JIT/AOT compilation. Perhaps you could link to an existing library such as LLVM or libjit.
I am evaluating different multiprocessing libraries for a fault tolerant application. I basically need any process to be allowed to crash without stopping the whole application.
I can do it using the fork() system call. The limit here is that the process can be created on the same machine, only.
Can I do the same with MPI? If a process created with MPI crashes, can the parent process keep running and eventually create a new process?
Is there any alternative (possibly multiplatform and open source) library to get the same result?
As reported here, MPI 4.0 will have support for fault tolerance.
If you want collectives, you're going to have to wait for MPI-3.something (as High Performance Mark and Hristo Illev suggest)
If you can live with point-to-point, and you are a patient person willing to raise a bunch of bug reports against your MPI implementation, you can try the following:
disable the default MPI error handler
carefully check every single return code from your MPI programs
keep track in your application which ranks are up and which are down. Oh, and when they go down they can never get back. but you're unable to use collectives anyway (see my opening statement), so that's not a huge deal, right?
Here's an old paper (back when Bill still worked at Argonne. I think it's from 2003):
http://www.mcs.anl.gov/~lusk/papers/fault-tolerance.pdf . It lays out the kinds of fault tolerant things one can do in MPI. Perhaps such a "constrained MPI" might still work for your needs.
If you're willing to go for something research quality, there's two implementations of a potential fault tolerance chapter for a future version of MPI (MPI-4?). The proposal is called User Level Failure Mitigation. There's an experimental version in MPICH 3.2a2 and a branch of Open MPI that also provides the interfaces. Both are far from production quality, but you're welcome to try them out. Just know that since this isn't in the MPI Standard, the function prefixes are not MPI_*. For MPICH, they're MPIX_*, for the Open MPI branch, they're OMPI_* (though I believe they'll be changing theirs to be MPIX_* soon as well.
As Rob Latham mentioned, there will be lots of work you'll need to do within your app to handle failures, though you don't necessarily have to check all of your return codes. You can/should use MPI error handlers as a callback function to simplify things. There's information/examples in the spec available along with the Open MPI branch.
I read about Just-in-time compilation (JIT) and as I understood, there are two approaches for this – Interpreter and JIT, both of which interpreting the bytecode at runtime.
Why not just preparatively interprete all the bytecode to machine code, and only then start to run the process with no more need for interpreter?
Another reason for late JIT compiling has to do with optimization: At run-time the VM can detect more/other patterns it may optimize than the compiler could ever do at compile-time. JIT pre-compiling at startup will always have to be static, and the same could have been done by the compiler already, but through analysis of the actual run-time behaviour the VM may have more information on possible optimizations and may therefore produce better optimization results.
For example, the VM can detect that a single piece of code is actually run a million times at run-time and perform appropriate optimizations which the compiler may have no information about, not unlike the branch prediction that's done at runtime in modern CPUs.
More information can be found in the Wikipedia article on "Adaptive optimization".
Simple: Because it takes time to precompile everything to machine code. And users don't want to wait on the application to start. Remember, the precompilation would have to make a lot of optimizations which takes time.
The server version of JVM is more aggressive in precompiling and optimizing code upfront because code on the server side tends to be executed more often and for a longer period of time before the process is shutdown.
However, a solution (for .Net) is an application called NGen which make the precompilation upfront such that it isn't needed after that point. You only have to run that once.
Not all VM's include an interpreter. For instance Chrome and CLR (.Net) always compiles to machine code before running. However, they have multiple levels of optimizations to reduce the startup time.
I found link showing how runtime recompilation can optimize performance and save extra CPU cycles.
Inlining expansion: To decrease the cost of procedure calls.
Removing redundant loads: When 2 compiled code results in some duplicate code then it can be removed and further optimised by recompilation at run time.
Copy propagation
Eliminating dead code
Here is another link for the same explanation given above.
I have a script that uses quicklisp to load zs3 for accessing Amazon's S3.
When I run the script with clisp, when (zs3:bucket-exists-p "Test") is run, USOCKET:TIMEOUT-ERROR occurs.
However, when I run it with sbcl, it runs properly.
Do they access usocket differently?
What are the pros and cons of each?
usocket is a compatibility layer which hides the underlying socket API of each Lisp implementation. There is bound to be an impedance mismatch in some cases, but for the most part it should just work.
I suspect zs3 is not often used with CLISP (or perhaps not at all!), and you're seeing the result of that. On the other hand one can generally expect libraries to be well-tested under SBCL since that is the most popular implementation.
Note also that threads are still experimental in CLISP; they are not enabled by default. The fact that sockets are often mixed with threads only decreases the relative use of CLISP + usocket.
I am working on lock free structure with g++ compiler. It seems that with -o1 switch, g++ will change the execution order of my code. How can I forbid g++'s optimization on certain part of my code while maintain the optimization to other part? I know I can split it to two files and link them, but it looks ugly.
If you find that gcc changes the order of execution in your code, you should consider using a memory barrier. Just don't assume that volatile variables will protect you from that issue. They will only make sure that in a single thread, the behavior is what the language guarantees, and will always read variables from their memory location to account for changes "invisible" to the executing code. (e.g changes to a variable done by a signal handler).
GCC supports OpenMP since version 4.2. You can use it to create a memory barrier with a special #pragma directive.
A very good insight about locking free code is this PDF by Herb Sutter and Andrei Alexandrescu: C++ and the Perils of Double-Checked Locking
You can use a function attribute "__attribute__ ((optimize 0))" to set the optimization for a single function, or "#pragma GCC optimize" for a block of code. These are only for GCC 4.4, though, I think - check your GCC manual. If they aren't supported, separation of the source is your only option.
I would also say, though, that if your code fails with optimization turned on, it is most likely that your code is just wrong, especially as you're trying to do something that is fundamentally very difficult. The processor will potentially perform reordering on your code (within the limits of sequential consistency) so any re-ordering that you're getting with GCC could potentially occur anyway.