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Towards scalable FPGA CAD through architecture

Published:27 February 2011Publication History

ABSTRACT

Long FPGA CAD runtime has emerged as a limitation to the future scaling of FPGA densities. Already, compile times on the order of a day are common, and the situation will only get worse as FPGAs get larger. Without a concerted effort to reduce compile times, further scaling of FPGAs will eventually become impractical.

Previous works have presented fast CAD tools that tradeoff quality of result for compile time. In this paper, we take a different but complementary approach. We show that the architecture of the FPGA itself can be designed to be amenable to fast-compile. If not done carefully, this can lead to lower-quality mapping results, so a careful tradeoff between area, delay, power, and compile run-time is essential. We investigate the extent to which run-time can be reduced by employing high-capacity logic blocks. We extend previous studies on logic block architectures by quantifying the area, delay and CAD runtime tradeoffs for large capacity blocks, and also investigate some multi-level logic block architectures. In addition, we present an analytically derived equation to guide the design of logic block I/O requirements.

References

  1. E. Ahmed and J. Rose. The effect of lut and cluster size on deep-submicron fpga performance and density. IEEE Trans. on VLSI, 12(3):288--298, March 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Altera. Apex20 family data sheets.Google ScholarGoogle Scholar
  3. R. Amerson, R. Carter, W. Culbertson, P. Kuekes, G. Snider, and L. Albertson. Plasma: an fpga for million gate systems. In Procs. of the Int'l Symp. on Field Programmable Gate Arrays, pages 10--16, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. V. Betz, J. Rose, and A. Marquardt. Architecture and cad for deep-submicron fpgas. Springer, pages ISBN 0-7923-8460-1, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. H. Bian, A. C. Ling, A. Choong, and J. Zhu. Towards scalable placement for fpgas. In Procs. of the Int'l Symp. on Field Programmable Gate Arrays, pages 147--156, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. S. Chin and S. Wilton. An analytical model relating fpga architecture and place and route runtime. In Procs. of the Int'l Conf. on Field-Programmable Logic and Applications, pages 146--153, Aug. 2009.Google ScholarGoogle Scholar
  7. J. Cong and Y. Ding. An optimal technology mapping algorithm for delay optimization in lookup-table based fpga designs. In Proc. of Int'l conf. on Computer-aided design, pages 48--53, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. Cong and M. Romesis. Performance-driven multi-level clustering with application to hierarchical fpga mapping. In Procs. of the Design Automation Conference, pages 389--394, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Dehkordi and S. Brown. Performance-driven recursive multi-level clustering. In Int'l Conf. on Field-Programmable Tech., pages 262--269, Dec. 2003.Google ScholarGoogle Scholar
  10. E. Hung, S. J. E. Wilton, H. Yu, T. C. P. Chau, and P. H. W. Leong. A detailed delay path model for fpgas. In Procs. of the Int'l Conf. on Field-Programmable Technology, pages 96--103, Dec. 2009.Google ScholarGoogle Scholar
  11. M. Hutton. Interconnect prediction for programmable logic devices. In Int'l workshop on System-level interconnect prediction, pages 125--131, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. A. Lam, S. Wilton, P. Leong, and W. Luk. An analytical model describing the relationships between logic architecture and fpga density. In Int'l Conf. on Field-Programmable Logic and Applications, 2008.Google ScholarGoogle Scholar
  13. G. Lemieux, E. Lee, M. Tom, and A. Yu. Directional and single-driver wires in fpga interconnect. In Int'l conf. on Field-Programmable Tech., pages 41--48, 2004.Google ScholarGoogle Scholar
  14. A. Ludwin, V. Betz, and K. Padalia. High-quality, deterministic parallel placement for fpgas on commodity hardware. In Procs. Int'l Symp. on Field programmable gate arrays, pages 14--23, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. Luu, I. Kuon, P. Jamieson, T. Campbell, A. Ye, W. M. Fang, and J. Rose. Vpr 5.0: Fpga cad and architecture exploration tools with single-driver routing, heterogeneity and process scaling. In Proc. of Int'l Symp. on FPGA, pages 133--142, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. C. Mark, A. Shui, and S. Wilton. A system-level stochastic circuit generator for fpga architecture evaluation. In Procs. of the Int'l Conf. on Field-Programmable Technology, 2008.Google ScholarGoogle Scholar
  17. A. Marquardt, V. Betz, and J. Rose. Speed and area tradeoffs in cluster-based fpga architectures. IEEE Trans. V. Large Scale Integr. Syst., 8(1):84--93, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. C. Mulpuri and S. Hauck. Runtime and quality tradeoffs in fpga placement and routing. In Int'l Symp on Field programmable gate arrays, pages 29--36, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. J. Pistorius and M. Hutton. Placement rent exponent calculation methods, temporal behaviour and fpga architecture evaluation. In workshop on System-level interconnect prediction, pages 31--38, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. K. K. W. Poon, S. J. E. Wilton, and A. Yan. A detailed power model for field-programmable gate arrays. ACM Trans. Design Automation of Electronic Systems, 10(2):279--302, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. D. P. Singh and S. D. Brown. Incremental placement for layout driven optimizations on fpgas. In Int'l Conf. on Computer-aided design, pages 752--759, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. R. Tessier. Fast placement approaches for fpgas. ACM Trans. Design Automation of Electronic Systems, 7(2):284--305, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. K. Vorwerk, A. Kennings, and J. W. Greene. Improving simulated annealing-based fpga placement with directed moves. Trans. Computer-Aided Design of Integrated Circuits and Systems, 28(2):179--192, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. A. G. Ye. Using the minimum set of input combinations to minimize the area of local routing networks in logic clusters containing logically equivalent i/os in fpgas. IEEE Trans. Very Large Scale Integr. Syst., 18(1):95--107, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. W. Zhao and Y. Cao. New generation of predictive technology model for sub-45nm early design exploration. IEEE Trans. Electron Devices, 53(11):2816--2823, 2006.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Conferences
      FPGA '11: Proceedings of the 19th ACM/SIGDA international symposium on Field programmable gate arrays
      February 2011
      300 pages
      ISBN:9781450305549
      DOI:10.1145/1950413

      Copyright © 2011 ACM

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      Publication History

      • Published: 27 February 2011

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