mpi

MPI - work/pool example

由 ぃ、小莉子 提交于 2020-01-11 07:14:51
问题 is there any example of using work/pool (or. Producer/Consumer) scheme for MPI? As for everything I have done, I am getting just one going through application and my app is deadlocked then. Thanks 回答1: Just googling around for "MPI Master Worker" or "MPI Master Slave", I see a bunch of examples; one good one hosted at Argonne National Labs is: http://www.mcs.anl.gov/research/projects/mpi/tutorial/mpiexmpl/src2/io/C/main.html 来源： https://stackoverflow.com/questions/5415074/mpi-work-pool

MPI - work/pool example

由 我的未来我决定 提交于 2020-01-11 07:14:47
问题 is there any example of using work/pool (or. Producer/Consumer) scheme for MPI? As for everything I have done, I am getting just one going through application and my app is deadlocked then. Thanks 回答1: Just googling around for "MPI Master Worker" or "MPI Master Slave", I see a bunch of examples; one good one hosted at Argonne National Labs is: http://www.mcs.anl.gov/research/projects/mpi/tutorial/mpiexmpl/src2/io/C/main.html 来源： https://stackoverflow.com/questions/5415074/mpi-work-pool

MPI - work/pool example

由 戏子无情 提交于 2020-01-11 07:14:21
问题 is there any example of using work/pool (or. Producer/Consumer) scheme for MPI? As for everything I have done, I am getting just one going through application and my app is deadlocked then. Thanks 回答1: Just googling around for "MPI Master Worker" or "MPI Master Slave", I see a bunch of examples; one good one hosted at Argonne National Labs is: http://www.mcs.anl.gov/research/projects/mpi/tutorial/mpiexmpl/src2/io/C/main.html 来源： https://stackoverflow.com/questions/5415074/mpi-work-pool

Shared memory access control mechanism for processes created by MPI

由 守給你的承諾、 提交于 2020-01-11 04:15:30
问题 I have a shared memory used by multiple processes, these processes are created using MPI . Now I need a mechanism to control the access of this shared memory. I know that named semaphore and flock mechanisms can be used to do this but just wanted to know if MPI provides any special locking mechanism for shared memory usage ? I am working on C under Linux. 回答1: MPI actually does provide support for shared memory now (as of version 3.0). You might try looking at the One-sided communication

Multi-GPU profiling (Several CPUs , MPI/CUDA Hybrid)

由 你离开我真会死。 提交于 2020-01-10 19:58:10
问题 I had a quick look on the forums and I don't think this question has been asked already. I am currently working with an MPI/CUDA hybrid code, made by somebody else during his PhD. Each CPU has its own GPU. My task is to gather data by running the (already working) code, and implement extra things. Turning this code into a single CPU / Multi-GPU one is not an option at the moment (later, possibly.). I would like to make use of performance profiling tools to analyse the whole thing. For now an

Corresponding Receive Routine of MPI_Bcast

由 烂漫一生 提交于 2020-01-10 13:32:29
问题 What would be the corresponding MPI receive routine of the broadcast routine, MPI_Bcast. Namely, one processor broadcasts a message to a group, let's say all world, how I can have the message in these processes? Thank you. Regards SRec 回答1: MPI_Bcast is both the sender and the receiver call. Consider the prototype for it. int MPI_Bcast ( void *buffer, int count, MPI_Datatype datatype, int root, MPI_Comm comm ) All machines except for the machine with id = root are receivers. The machine that

Python多核编程mpi4py实践

由 隐身守侯 提交于 2020-01-10 07:37:54
Python多核编程mpi4py实践 一、概述 CPU从三十多年前的8086，到十年前的奔腾，再到当下的多核i7。一开始，以单核cpu的主频为目标，架构的改良和集成电路工艺的进步使得cpu的性能高速上升，单核cpu的主频从老爷车的MHz阶段一度接近4GHz高地。然而，也因为工艺和功耗等的限制，单核cpu遇到了人生的天花板，急需转换思维，以满足无止境的性能需求。多核cpu在此登上历史舞台。给你的老爷车多加两个引擎，让你有法拉利的感觉。现时代，连手机都到处叫嚣自己有4核8核处理器的时代，PC就更不用说了。 扯远了，anyway，对于俺们程序员来说，如何利用如此强大的引擎完成我们的任务才是我们要考虑的。随着大规模数据处理、大规模问题和复杂系统求解需求的增加，以前的单核编程已经有心无力了。如果程序一跑就得几个小时，甚至一天，想想都无法原谅自己。那如何让自己更快的过度到高大上的多核并行编程中去呢？哈哈，广大人民的力量！ 目前工作中我所接触到的并行处理框架主要有MPI、OpenMP和MapReduce(Hadoop)三个（CUDA属于GPU并行编程，这里不提及）。MPI和Hadoop都可以在集群中运行，而OpenMP因为共享存储结构的关系，不能在集群上运行，只能单机。另外，MPI可以让数据保留在内存中，可以为节点间的通信和数据交互保存上下文，所以能执行迭代算法，而Hadoop却不具有这个特性

mpi4py 快速上手

由 一个人想着一个人 提交于 2020-01-10 05:49:15
在 上一篇 中我们介绍了如何安装和使用 mpi4py，下面我们以几个简单的例子来展示怎么使用 mpi4py 来进行并行编程，以使读者能够快速地上手使用 mpi4py。这些例子来自 mpi4py 的 Document ，有些做了一些适当的改动。 点到点通信 传递通用的 Python 对象（阻塞方式） 这种方式非常简单易用，适用于任何可被 pickle 系列化的 Python 对象，但是在发送和接收端的 pickle 和 unpickle 操作却并不高效，特别是在传递大量的数据时。另外阻塞式的通信在消息传递时会阻塞进程的执行。 # p2p_blocking.py from mpi4py import MPI comm = MPI.COMM_WORLD rank = comm.Get_rank() if rank == 0: data = {'a': 7, 'b': 3.14} print 'process %d sends %s' % (rank, data) comm.send(data, dest=1, tag=11) elif rank == 1: data = comm.recv(source=0, tag=11) print 'process %d receives %s' % (rank, data) 运行结果如下： $ mpiexec -n 2 python p2p

Unable to implement MPI_Intercomm_create

由 ⅰ亾dé卋堺 提交于 2020-01-07 07:44:06
问题 I am trying to implement an MPI_intercomm in Fortran between 2 inter communicators, one which has first 2 process and the other having the rest. I need to perform send, recv operations between the newly created communicators. The code: program hello include 'mpif.h' integer tag,ierr,rank,numtasks,color,new_comm,inter1,inter2 tag = 22 call MPI_Init(ierr) call MPI_COMM_RANK(MPI_COMM_WORLD,rank,ierr) call MPI_COMM_SIZE(MPI_COMM_WORLD,numtasks,ierr) if (rank < 2) then color = 0 else color = 1 end

Controlling node mapping of MPI_COMM_SPAWN

由 穿精又带淫゛_ 提交于 2020-01-07 05:39:10
问题 The context: This whole issue can be summarized that I'm trying replicate the behaviour of a call to system (or fork ), but in an mpi environment. (Turns out that you can't call system in parallel.) Meaning I have a program running on many nodes, one process on each node, and then I want each process to call an external program (so for n nodes I'd have n copies of the external program running), wait for all those copies to finish, then keep running the original program. To achieve this in a
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