multicore

Does Java have support for multicore processors/parallel processing?

穿精又带淫゛_ 提交于 2019-11-27 02:55:36
I know that now that most processors have two or more cores, multicore programming is all the rage. Is there functionality to utilize this in Java? I know that Java has a Thread class, but I also know this was around a long time before multicores became popular. If I can make use of multiple cores in Java, what class/technique would I use? bakkal 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

How do I time out a lapply when a list item fails or takes too long?

偶尔善良 提交于 2019-11-27 02:43:43
问题 For several efforts I'm involved in at the moment, I am running large datasets with numerous parameter combinations through a series of functions. The functions have a wrapper (so I can mclapply ) for ease of operation on a cluster. However, I run into two major challenges. a) My parameter combinations are large (think 20k to 100k). Sometimes particular combinations will fail (e.g. survival is too high and mortality is too low so the model never converges as a hypothetical scenario). It's

Compiling with g++ using multiple cores

爱⌒轻易说出口 提交于 2019-11-27 02:27:27
Quick question: what is the compiler flag to allow g++ to spawn multiple instances of itself in order to compile large projects quicker (for example 4 source files at a time for a multi-core CPU)? You can do this with make - with gnu make it is the -j flag (this will also help on a uniprocessor machine). For example if you want 4 parallel jobs from make: make -j 4 You can also run gcc in a pipe with gcc -pipe This will pipeline the compile stages, which will also help keep the cores busy. If you have additional machines available too, you might check out distcc , which will farm compiles out

could not find function inside foreach loop

回眸只為那壹抹淺笑 提交于 2019-11-27 01:21:32
问题 I'm trying to use foreach to do multicore computing in R. A <-function(....) { foreach(i=1:10) %dopar% { B() } } then I call function A in the console. The problem is I'm calling a function Posdef inside B that is defined in another script file which I source. I had to put Posdef in the list of export argument of foreach : .export=c("Posdef") . However I get the following error: Error in { : task 3 failed - "could not find function "Posdef"" Why cant R find this defined function? 回答1: The

CPU TSC fetch operation especially in multicore-multi-processor environment

倾然丶 夕夏残阳落幕 提交于 2019-11-27 01:13:15
In Linux world, to get nano seconds precision timer/clockticks one can use : #include <sys/time.h> int foo() { timespec ts; clock_gettime(CLOCK_REALTIME, &ts); //--snip-- } This answer suggests an asm approach to directly query for the cpu clock with the RDTSC instruction. In a multi-core, multi-processor architecture, how is this clock ticks/timer value synchronized across multiple cores/processors? My understanding is that there in inherent fencing being done. Is this understanding correct? Can you suggest some documentation that would explain this in detail? I am interested in Intel Nehalem

Functional programming and multicore architecture

夙愿已清 提交于 2019-11-27 01:02:18
问题 I've read somewhere that functional programming is suitable to take advantage of multi-core trend in computing. I didn't really get the idea. Is it related to the lambda calculus and von neumann architecture? 回答1: Functional programming minimizes or eliminates side effects and thus is better suited to distributed programming. i.e. multicore processing. In other words, lots of pieces of the puzzle can be solved independently on separate cores simultaneously without having to worry about one

Python: Multicore processing?

本小妞迷上赌 提交于 2019-11-27 00:14:33
问题 I've been reading about Python's multiprocessing module. I still don't think I have a very good understanding of what it can do. Let's say I have a quadcore processor and I have a list with 1,000,000 integers and I want the sum of all the integers. I could simply do: list_sum = sum(my_list) But this only sends it to one core. Is it possible, using the multiprocessing module, to divide the array up and have each core get the sum of it's part and return the value so the total sum may be

What parallel programming model do you recommend today to take advantage of the manycore processors of tomorrow?

十年热恋 提交于 2019-11-26 23:49:55
问题 If you were writing a new application from scratch today, and wanted it to scale to all the cores you could throw at it tomorrow, what parallel programming model/system/language/library would you choose? Why? I am particularly interested in answers along these axes: Programmer productivity / ease of use (can mortals successfully use it?) Target application domain (what problems is it (not) good at?) Concurrency style (does it support tasks, pipelines, data parallelism, messages...?)

Do the new C# 5.0 'async' and 'await' keywords use multiple cores?

坚强是说给别人听的谎言 提交于 2019-11-26 23:49:52
Two new keywords added to the C# 5.0 language are async and await , both of which work hand in hand to run a C# method asynchronously without blocking the calling thread. My question is, do these methods actually take advantage of multiple cores and run in parallel or does the async method run in the same thread core as the caller? Two new keywords added to the C# 5.0 language are async and await, both of which work hand in hand to run a C# method asynchronously without blocking the calling thread. That gets across the purpose of the feature, but it gives too much "credit" to the async/await

Threads & Processes Vs MultiThreading & Multi-Core/MultiProcessor : How they are mapped?

随声附和 提交于 2019-11-26 23:49:19
问题 I was very confused but the following thread cleared my doubts: Multiprocessing, Multithreading,HyperThreading, Multi-core But it addresses the queries from the hardware point of view. I want to know how these hardware features are mapped to software? One thing that is obvious is that there is no difference between MultiProcessor(=Mutlicpu) and MultiCore other than that in multicore all cpus reside on one chip(die) where as in Multiprocessor all cpus are on their own chips & connected