Does Java have support for multicore processors/parallel processing? Yes. It also has been a platform for other programming languages where the implementation added a “true multithreading” or “real threading” selling point. The G1 Garbage Collector introduced in newer releases also makes use of multi-core hardware. Java Concurrency in Practice Try to get a copy of … Read more
Another very handy way to do this is with gnu parallel, which is well worth installing if you don’t already have it; this is invaluable if the tasks don’t necessarily take the same amount of time. seq 1000 | parallel -j 8 –workdir $PWD ./myrun {} will launch ./myrun 1, ./myrun 2, etc, making sure … Read more
i use exec(). Its easy and clean. You basically need to build a thread manager, and thread scripts, that will do what you need. I dont like fsockopen() because it will open a server connection, that will build up and may hit the apache’s connection limit I dont like curl functions for the same reason … Read more
map_partitions You can apply your function to all of the partitions of your dataframe with the map_partitions function. df.map_partitions(func, columns=…) Note that func will be given only part of the dataset at a time, not the entire dataset like with pandas apply (which presumably you wouldn’t want if you want to do parallelism.) map / … Read more
. I sent an email to OpenMP developers about this subject, the answer I got: For signed int, the wrap around behavior is undefined. If we allow !=, programmers may get unexpected tripcount. The problem is whether the compiler can generate code to compute a trip count for the loop. For a simple loop, like: … Read more
You can use a concurrent collection. The System.Collections.Concurrent namespace provides several thread-safe collection classes that should be used in place of the corresponding types in the System.Collections and System.Collections.Generic namespaces whenever multiple threads are accessing the collection concurrently. You could for example use ConcurrentBag since you have no guarantee which order the items will be … Read more
In the 2009-2012 period, the following things have happened: 2012: From 2012, the parallel Haskell status updates began appearing in the Parallel Haskell Digest. 2011: Parallel and Concurrent Programming in Haskell, a tutorial. version 1.1 released by Simon Marlow Haskell and parallelism, mentioned in an article in the Economist magazine, Jun 2nd 2011. Parallel tree … Read more
For this kind of job a powerful tool you could use is the TPL Dataflow library. With this tool you can create a processing pipeline consisting of many linked blocks, with the data flowing from the first block to the last (circles and meshes are also possible). The advantages of this approach are: You get … Read more
I think it’s likely that the fastest performance will be achieved by using the CUBLAS batch gemm function which was specifically designed for this purpose (performing a large number of “relatively small” matrix-matrix multiply operations). Even though you want to multiply your array of matrices (M[]) by a single matrix (N), the batch gemm function … Read more
This happens because you didn’t protect your “procedural” part of the code from re-execution when your child processes are importing f. They need to import f, because Windows doesn’t support forking as start method for new processes (only spawn). A new Python process has to be started from scratch, f imported and this import will … Read more