ECE 506 Reconfigurable Computing Lecture 8 FPGA Placement

1. ECE 506Reconfigurable ComputingLecture 8FPGA Placement

2. Timing-driven Placement • Why should placement take timing into account? • Placement sets the constraints for router • A timing driven router’s performance is limited by the quality of the placement. • For more speed, placement should be timing-driven. • Operation principle • Map blocks that are on critical path onto physical locations that are closer together • Minimize the amount of interconnect for critical signals to traverse

3. Timing-Driven Placement Expectation • High quality placement • Reasonable execution time • Less sacrifices in routability

4. Timing-driven Placement • Timing-driven only placement • Increases demand on routing resources • Wireability-driven only placement • Slower circuit • Take both wire length and critical path into account • Problem: Modeling delay • Critical path changes as we move blocks • Most accurate delay model • Route each placement • Extract delay of each connection • Execution time is a major problem

5. Timing-Driven Placement – Delay Modeling • Delay profile • Homogenous FPGA • Exploit uniformity • Compute delay as a function of distance (∆x, ∆y) • Use VPR router to determine delay between blocks • Compute a delay lookup matrix for every possible ∆x, ∆y • Router is timing driven • Take advantage of the architecture features • Segment length • Use long wires for blocks on far ends of the FPGA • Assumption that router will probably find the minimum delay path (a leap of faith!)

6. Determining Criticality • Same basic approach as used for clustering criticality • For each (i, j) connection from source i and sink j • Determine arrival times (pre-order BFS) • Determine required arrival times (post-order BFS) • Determine slack -> required_arrival_time – arrival_time • Criticality(i, j) = [1- slack(i, j)]/ (Max slack)

7. TVPLACE

8. Cost Function From lookup table matrix [0 1] What is the purpose of the criticality exponent? • Heavily weight connections that are critical, while giving less weight to connections that are non-critical

9. Balancing Wiring and Timing Cost • Need to determine relative changes in timing and wiring based on moves • Idea: Use relative changes from previous calculation • Both values less than 1 • Helps balance effect based on scaling parameter

10. Path vs Connection Based Timing Analysis • Path based: • Timing-analysis to compute path-delays at every stage of the placement and use delays in the cost function • Computationally expensive • Moving any connection triggers a new timing-analysis • Connection based: • Perform timing-analysis before placement • Assign slacks to each connection • Pay attention to connections with low slack • Delay values are always up to date (∆x, ∆y) • Criticality becomes outdated after the moves • Approach: Hybrid • Allow certain number of moves between each timing-analysis

11. VPR, Placement • VPlace is a Simulated Annealing based algorithm • minimize the amount of interconnect • circuit blocks that are on the same net => close together. • uses a bounding-box based cost function

12. Updated Annealing Algorithm

13. How often to recalculate delay? • Recalculating delay once per temperature is good. • Also simplifies programming somewhat # of temperature changes between each timing analysis

14. Criticality Exponent • Large exponent • Fewer connections will have large “Timing_Cost” • For these few connections “Timing_Cost” is effective • For Non-critical connections “Wiring_Cost” is effective • Therefore, placement focuses on minimizing wiring as “Criticality_Exponent” increases

15. Criticality Exponent • When  is 1 • Critical path is worse • Wiring cost is much more worse

16. Oscillation Effect • When  is 1 • Only delay component • Attempts to minimize critical path at the cost of extending other non-critical paths • Timing analyze once per temperature update • Several moves between temperature updates • Able to reduce critical path during one iteration of the outer loop • Makes other paths very critical • Oscillation effect makes it hard for placement to converge to best solution • When  is 0.5 • Wirelength reduces the oscillation effect • Penalizes moves that increase wirelength

17. Effect of 

18. How important is timing-driven placement? Run time Penalty – 2.5X

19. Conclusion • The greatest challenge facing FPGA placement is the need to produce high quality placements for ever-larger circuits. • FPGA capacity doubles every two to three years, doubling the size of the placement problem. • In order to maintain the fast time to market and ease of use historically provided by FPGAs, placement algorithms cannot be allowed to take ever more CPU time. • There is thus a compelling need for algorithms that are very scalable and parallel yet still produce high-quality results.