CS 584 Lecture7

1. CS 584 Lecture7 • Assignment -- Due Now! • Paper Review is due next week. • JPDC • IEEE Concurrency • IEEE Transactions on Parallel and Distributed Systems • Conference Proceedings (see me)

2. Review • Partition • Communication • Agglomeration • Mapping • Place tasks on physical processors

3. Floorplan Optimization • VLSI Design • Computation used in many stages • Verify Correctness of Circuit Design • Circuit Layout • Circuit Test Pattern Generation

4. VLSI Design Stages • Generate a set of indivisible cells (rectangular blocks) • Use interconnection information for relative placement • Place cells with goal of optimizing the total area. • Floorplan optimization

5. Floorplan Optimization • Cells have different sizes and can be in a few different configurations.

6. Floorplan Optimization • Relative placements of the cells is represented by two graphs G and H Up-Down Left-Right

7. Floorplan Optimization • Using the G and H graphs we can generate alternative floorplans

8. Floorplan Optimization • Identify the configuration with the lowest area. • Explore a search tree representing all configurations • Exhaustive search infeasible • 20 cells with 6 configurations each • 620 ~ 4 x 1015 nodes

9. Branch and Bound Search • Reduces the number of nodes searched. • Keep track of the best solution • Prune the search by not expanding nodes whose solution is worse than the best known solution.

10. Floorplan Optimization Place A Place B Place C

11. Parallelization • Branch and Bound search is the computational effort to be parallelized. • Irregular computational structure • Pruning introduces • Search order management • Propagation of global knowledge

12. Partition • No obvious domain to decompose. • Functional decomposition • Each search tree node explored by a different task • Wavefront • Only tasks on the wavefront can execute concurrently.

13. Communication • All tasks must have best known solution. • Trade-off • benefits of always having best solution • communication costs • Can use centralized scheme or hierarchical refinement

14. Agglomeration • A large search space can generate a huge number of tasks. • Create a new task for each node of the tree until we reach a certain point

15. Mapping • Task scheduling algorithm • Workers request tasks and generate tasks to be worked on by others • Find a mapping that works with the agglomeration scheme.

16. Mapping Strategies • Central manager • Generates coarse grain tasks • Replication with cyclic mapping • Everybody expands tree • Everybody knows their responsibility • Hierarchical • Each node manages its subtree

17. PCAM Design Summary • Partition problem into small tasks • Organize the necessary communication. • Agglomerate to decrease communication • Map tasks to processors • Pay attention to Performance!