1 / 18

Hybrid Programming with OpenMP and MPI

Hybrid Programming with OpenMP and MPI. Kushal Kedia Reacting Gas Dynamics Laboratory 18.337J –Final Project Presentation, May 13 th 2009 kushal@mit.edu. Motivation – Flame dynamics. 8 processors on single shared memory, pure OpenMP

cachez
Download Presentation

Hybrid Programming with OpenMP and MPI

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hybrid Programming with OpenMP and MPI Kushal Kedia Reacting Gas Dynamics Laboratory 18.337J –Final Project Presentation, May 13th 2009 kushal@mit.edu

  2. Motivation – Flame dynamics • 8 processors on single shared memory, pure OpenMP • 2 cycles of 200 Hz flame oscillation (0.01 seconds of real time) takes approximately 5 days!

  3. MPI – Message Passing Interface Cluster of Computers OpenMP – Open Multi Processing Desktop MPI? OpenMP? Symmetric Multiprocessing (SMP)

  4. Network Connection Modern Clusters (multiple SMPs)

  5. Pros Portable to distributed and shared memory machines. Scales beyond one node No data placement problem Cons Difficult to develop and debug High latency, low bandwidth Explicit communication Difficult load balancing Pros Easy to implement parallelism Low latency, high bandwidth Implicit Communication Dynamic load balancing Cons Only on shared memory machine Scale within one node Possible data placement problem No specific thread order MPI OpenMP

  6. Why Hybridization? – best from both the paradigms • introducing MPI into OpenMP applications can help scale across multiple SMP nodes • introducing OpenMP into MPI applications can help make more efficient use of the shared memory on SMP nodes, thus mitigating the need for explicit intra-node communication • introducing MPI and OpenMP during the design/coding of a new application can help maximize efficiency, performance, and scaling

  7. Problem Statement Steady-State Heat Transfer Like Problem

  8. Solution

  9. Distribution among 4 processors Grid and parallel Decomposition

  10. MPI Scenario • Each chunk of the grid goes to a separate processor • Explicit communication calls are made after every iteration, irrespective of the processor being on the same SMP node or different

  11. Hybrid Scenario • A single MPI process on each SMP node • Each process spawns 4 threads, which carries out OpenMP iterations • Master thread of each SMP node communicates after every iteration

  12. MASTER THREADS of respective SMP nodes Schematic Hybrid Scenario

  13. Computational resources • Pharos cluster (a shared and distributed memory architecture), used by the Reacting Gas Dynamics Laboratory (Dept. of Mechanical Engineering, MIT) is used for the parallel simulations. • Pharos consists of about 60 Intel Xeon -Harpertown nodes, each consisting of dual quad-core CPUs (8 processors) of 2.66 GHz speed.

  14. Fixed grid size of 2500 x 2500

  15. Constant # of processors = 20

  16. Hybrid Program slower than pure MPI! Seen with many problems. Cases with Hybrid programs faster than pure MPI are few, but work very well if suitable

  17. Why? Possible arguments • Less scalability of OpenMP due to implicit parallelism • All threads idle except one while inter-node communication is taking place • Cache Miss high due to larger dataset and data placement problem • Lack of optimized OpenMP libraries compared to MPI libraries • Communication/computation ratio is low

  18. References

More Related