mpi

Process Pinning

由 北战南征 提交于 2020-02-07 14:18:10
https://software.intel.com/en-us/mpi-developer-reference-linux-process-pinning Process Pinning Use this feature to pin a particular MPI process to a corresponding CPU within a node and avoid undesired process migration. This feature is available on operating systems that provide the necessary kernel interfaces. Processor Identification The following schemes are used to identify logical processors in a system: System-defined logical enumeration Topological enumeration based on three-level hierarchical identification through triplets (package/socket, core, thread) The number of a logical CPU is

Using valgrind to spot error in mpi code

由 青春壹個敷衍的年華 提交于 2020-01-28 04:54:46
问题 I have a code which works perfect in serial but with mpirun -n 2 ./out it gives the following error: ./out': malloc(): smallbin double linked list corrupted: 0x00000000024aa090 I tried to use valgrind such as: valgrind --leak-check=yes mpirun -n 2 ./out I got the following output: ==3494== Memcheck, a memory error detector ==3494== Copyright (C) 2002-2015, and GNU GPL'd, by Julian Seward et al. ==3494== Using Valgrind-3.11.0 and LibVEX; rerun with -h for copyright info ==3494== Command:

Errors caused by write statements when running f2py-wrapped, PETSc-based fortran code in OpenMDAO

由 无人久伴 提交于 2020-01-25 22:05:51
问题 I am using f2py to wrap my PETSc-based fortran analysis code for use in OpenMDAO (as suggested in this post). Rather than use f2py directly, I'm instead using it to generate the relevant .c, .pyc, etc. files and then linking them myself using mpif90. In a simple python environment, I can import my .so and run the code without any problems: >>> import module_name >>> module_name.execute() expected code output... However, when trying to do the same thing in an OpenMDAO component, I get the

Errors caused by write statements when running f2py-wrapped, PETSc-based fortran code in OpenMDAO

由 佐手、 提交于 2020-01-25 22:05:32
问题 I am using f2py to wrap my PETSc-based fortran analysis code for use in OpenMDAO (as suggested in this post). Rather than use f2py directly, I'm instead using it to generate the relevant .c, .pyc, etc. files and then linking them myself using mpif90. In a simple python environment, I can import my .so and run the code without any problems: >>> import module_name >>> module_name.execute() expected code output... However, when trying to do the same thing in an OpenMDAO component, I get the

Block execution until children called via MPI_Comm_spawn have finished

由 為{幸葍}努か 提交于 2020-01-25 06:36:09
问题 I'm in the process of modifying an existing application, where I would like to spawn a dynamically created bash script. I created a simple wrapper routine which takes the name of the bash script as an argument. In the wrapper, the script is spawned by MPI_Comm_spawn. Directly after, the wrapper calls MPI_Finalize, which is executed before the scripts have finished: #include "mpi.h" #include <stdlib.h> #include <iostream> using namespace std; int main(int argc, char *argv[]) { char *script =

Block execution until children called via MPI_Comm_spawn have finished

由 强颜欢笑 提交于 2020-01-25 06:35:08
问题 I'm in the process of modifying an existing application, where I would like to spawn a dynamically created bash script. I created a simple wrapper routine which takes the name of the bash script as an argument. In the wrapper, the script is spawned by MPI_Comm_spawn. Directly after, the wrapper calls MPI_Finalize, which is executed before the scripts have finished: #include "mpi.h" #include <stdlib.h> #include <iostream> using namespace std; int main(int argc, char *argv[]) { char *script =

MPI matrix-vector-multiplication returns sometimes correct sometimes weird values

由 谁都会走 提交于 2020-01-24 04:20:06
问题 I have the following code: //Start MPI... MPI_Init(&argc, &argv); int size = atoi(argv[1]); int delta = 10; int rnk; int p; int root = 0; MPI_Status mystatus; MPI_Comm_rank(MPI_COMM_WORLD, &rnk); MPI_Comm_size(MPI_COMM_WORLD, &p); //Checking compatibility of size and number of processors assert(size % p == 0); //Initialize vector... double *vector = NULL; vector = malloc(size*sizeof(double)); double *matrix = NULL; //Rank 0 ----------------------------------- if (rnk == 0) { //Initialize

Sending typedef struct containing void* by creating MPI drived datatype.

由 守給你的承諾、 提交于 2020-01-23 13:55:16
问题 what I understand studying MPI specification is that an MPI send primitive refer to a memory location (or a send buffer) pointed by the data to be sent and take the data in that location which then passed as a message to the another Process. Though it is true that virtual address of a give process will be meaningless in another process memory address; It is ok to send data pointed by pointer such as void pointer as MPI will any way pass the data itself as a message For example the following

Sending typedef struct containing void* by creating MPI drived datatype.

由 邮差的信 提交于 2020-01-23 13:51:10
问题 what I understand studying MPI specification is that an MPI send primitive refer to a memory location (or a send buffer) pointed by the data to be sent and take the data in that location which then passed as a message to the another Process. Though it is true that virtual address of a give process will be meaningless in another process memory address; It is ok to send data pointed by pointer such as void pointer as MPI will any way pass the data itself as a message For example the following

mpi4py 的一些使用技巧

由 血红的双手。 提交于 2020-01-22 09:35:16
在 上一篇 中我们介绍了 mpi4py 中的访问文件数据操作方法，至此 mpi4py 中最主要的内容已经基本介绍完毕，下面我们将介绍 mpi4py 的一些使用技巧。 兼容非 MPI 编程 从前面的介绍可知，使用 mpi4py 进行 Python 环境下的 MPI 编程是比较容易的，在不牺牲 Python 本身的灵活性和易用性的基础上，mpi4py 可以使我们轻松地利用多核甚至多计算节点进行并行甚至分布式的计算任务，以显著地提高计算效率。但是在有些情况下，我们却必须在非 MPI 环境下运行我们的程序，或者做相应的计算。为我们的并行计算程序再准备一个非并行的版本是一种解决方案，但是却要付出额外的劳动，对大型的或特别复杂的应用程序，维护两个版本的程序可能需要很高的成本，而且容易出错。一种更好的方案是让我们的并行计算程序也能兼容非 MPI 编程环境，也就是说，在 MPI 环境下，就利用多个进程以加速程序的计算，但是在非 MPI 环境下，就回归到单进程的串行程序，在可能花费更多时间的情况下完成所需的计算。使用 mpi4py 并行编程时怎么做到这一点呢？使用 mpi4py 做并行计算，一般需要导入 mpi4py 中的 MPI 模块，在非 MPI 环境下这一导入过程会出错（抛出 ImportError 异常），我们可以使用 Python 的异常处理机制捕获这一异常，使程序能够顺利执行
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