Question #699458 on Yade changed: https://answers.launchpad.net/yade/+question/699458
Robert Caulk posted a new comment: Hello Ziyu, I appreciate the curiosity for the code, but I must admit, it is a bit frustrating to re-answer this same question 5 times per year in this forum. Please consider searching through the forum a bit more deeply before requesting our assistance. The reason I add information here is because you've made incorrect statements about Yade OpenMP and MPI, and thus I need to correct the record. >>The current - j option implements multithreaded parallel computing through OpenMP, but this method is limited at present. You may be a bit mistaken here. Yade's OpenMP implementation is, in no way, "limited." It is quite robust, effective, debugged, and working in many different aspects of the code. What you believe to be "limited" is that you cannot speed up a 2000 particle simulation with 96 cores. This is the same case for all OpenMP applications, it is not *unique* to yade. So let's be clear there is nothing wrong or "limited" with Yade's implementation of OpenMP. >> So I assume that for "basic" settings, the own computer is just simply faster than the workstation. I confirm Jan's answer here. "Workstations" (high core count computers) are not designed to be the best at single threaded applications. They are designed for large parallelizable problems. Home desktops are designed to load facebook quickly. Hence the focus on higher clock speed than core count. I dont think anyone, in any computational field, would consider 2000 particles to be considered a large parallelizable problem. >>MPI[1] is another parallel computing method, and I can adjust the >>multithreaded openMPI computing for Yade using. >>However, I am not involved in the project and don't know if / how it works, >>its limitations etc. MPI* is in fact another parallel computing method. However, I do not know what "adjust multithreaded openMPI" means. To summarize MPI, it is allowing separate computers to work on the same problem. In comparison OpenMP, shared memory, is allowing separate cores of a single CPU to work on the same problem. As you can imagine the MPI implementation is much more difficult for implementation, and the communication between computers takes time. So no, MPI will *NOT* speed up your 2000 particle problem. IT will certainly slow it down. Also keep in mind that MPI is relatively new to yade, so there is a higher risk of encountering bugs, relative to OpenMP. Additionally you should consider that using MPI in yade requires at least some fundamental knowledge of how MPI works, so that you are setting up the problem correctly. In comparison, OpenMP requires zero knowledge from a coding perspective. -rc -- You received this question notification because your team yade-users is an answer contact for Yade. _______________________________________________ Mailing list: https://launchpad.net/~yade-users Post to : [email protected] Unsubscribe : https://launchpad.net/~yade-users More help : https://help.launchpad.net/ListHelp
