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Short Course on Advanced Course on Multi-Threaded Parallel Programming using OpenMP for Multicore/Manycore Systems
 
9:00 - 17:00 on Saturdays, August 22 - September 5, 2020
Cisco Webex, Online seminar

Speaker:
Kengo Nakajima (University of Tokyo)


Organizers:
Weichung Wang (National Taiwan University)


一、 課程背景與目的:
In order to make full use of modern supercomputer systems with multicore/manycore
architectures, hybrid parallel programming with message-passing and multithreading is essential. While MPI is widely used for message-passing, OpenMP for CPU and OpenACC for GPU are the most popular ways for multithreading on multicore/manycore clusters. In this 3-day course, we focus on optimization of single node performance using OpenMP for CPU. We “parallelize” a finite-volume method (FVM) code with Krylov iterative solvers for Poisson’s equation on Oakbridge-CX supercomputer (OBCX) at the University of Tokyo with 6.6 PF peak performance (https://www.cc.u-tokyo.ac.jp/en/supercomputer/obcx/system.php), which consists of the most recent CPU’s (Intel Xeon Platinum 8280 (Cascade Lake, CLX).
 
二、課程之大綱與講者:
In this Summer School, the target application is a 3D FVM code for Poisson’s equation by ICCG Method (Conjugate Gradient (CG) iterative method with Incomplete Cholesky preconditioning), which is widely-used in practical applications. Because ICCG includes “data dependency”, where writing/reading data to/from memory could occur simultaneously, parallelization using OpenMP is not straight forward. We need certain kind of reordering in order to extract parallelism. In this 3-day course, lectures and exercise on the following issues will be provided:
1. Overview of Finite-Volume Method (FVM)
2. Kyrilov Iterative Method, Preconditioning
3. Implementation of the Program
4. Introduction to OpenMP
5. Reordering/Coloring Method
6. Parallel FVM by OpenMP
 
三、課程詳細時間地點以及方式:
August 22, 2020
●Introduction
●Finite Volume Method (FVM)
August 29, 2020
●Introduction to OpenMP
●Reordering
September 5, 2020
●Reordering
●Parallel FVM by OpenMP
 





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 (C) 2019 National Center for Theoretical Sciences