Abstract
Reasonable trade-off between the ASIC performance and GPP flexibility is the main objective of reconfigurable computing systems. Dynamic Reconfigurable computing platform using embedded just-in-time (JIT) compilation is the most flexible platform among others. All complex computing kernels can be translated to bitstream to be executed on FPGA using an embedded processor of dedicated specialized hardware. The main challenge in these systems is FPGA design automation time. Executing the CAD algorithms on embedded processor is too time-consuming and normally is not feasible for real applications. Placement is the most computative part of CAD algorithm. Therefore, a new FPGA placement algorithm is proposed in this paper which makes reasonable trade-off between execution time and quality of placement. The proposed algorithm includes two stages: force-directed placement and simulated annealing placement. The proposed algorithm is very low execution time to be useful in JIT compilation without considerable degradation on the quality of placement. Experimental results show \(2.33\times \) speedup in execution time in cost of 3 % overhead in channel tracks numbers.
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References
Koester M, Hagemeyer J, Porrmann M (2011) Design optimizations for tiled partially reconfigurable systems. IEEE Trans VLSI Syst 19(6):1048–1061. doi:10.1109/TVLSI.2010.2044902
Kingshuk K, Chattopadhyay A, Chen X, Kammler D, Hao L, Leupers R, Meyr H, Ascheid G (2008) A design flow for architecture exploration and implementation of partially reconfigurable processors. IEEE Trans VLSI Syst 16(10):1281–1294
Marconi T (2014) Online scheduling and placement of hardware tasks with multiple variants on dynamically reconfigurable field-programmable gate arrays. Comput. Electr. Eng. 40(4):1215–1237
Fazlali M, Zakerolhosseini A, Gaydadjiev G (2012) Efficient datapath merging for the overhead reduction of run-time reconfigurable systems. J Supercomput 59(2):636–657
Sidiropoulos H, Siozios K (2012) On Supporting efficient partial reconfiguration with just-in-time compilation, IPDPS workshops, pp 328–335
Bergeron E, Feeley M, David J (2008) Hardware JIT compilation for off-the-shelf dynamically reconfigurable FPGAs. In: 17th international conference, CC, pp 178–192
Lysecky R, Vahid F, Tan S (2004) Dynamic FPGA routing for just-in-time FPGA compilation. In: Proceedings of the 41st design automation conference, 2004. IEEE, San Diego, CA, pp 954–959
Vahid F, Stitt G, Lysecky R (2008) Warp processing: dynamic translation of binaries to FPGA circuits. IEEE Comput Soc 41(7):40–46
Lysecky R, Vahid F (2009) Design and implementation of a microblaze-based warp processor. ACM Tran Embed Comput Syst (TECS) 8(3):21–29
Grudnitsky A, Bauer L (2012) Partial online-synthesis for mixed-grained reconfigurable architectures. Des Autom Test Europe Conf (DATE), pp 1555–1560
Bauer L, Shafique M, Kreutz S, Henkel J (2008) Run-time system for an extensible embedded processor with dynamic instruction set. Des Autom Test Eur, 752–757
Coole J, Stitt G (2014) Fast, flexible high-level synthesis from OpenCL using reconfiguration contexts. Micro IEEE 34(1):42–53
Shaoshan L, Richard P, Alessandro F, Gaudiot J (2012) Minimizing the runtime partial reconfiguration overheads in reconfigurable systems. J Supercomput 61(3):894–911
Jang S, Chan B, Chung K (2009) WireMap: FPGA technology mapping for improved routability and enhanced LUT merging. ACM Trans Reconfig Technol Syst 2(2):1–23
Sanjabi M, Miralaei N, Amanollahi S, Jahanian A (2012) ParSA: parallel simulated annealing placement algorithm for multi-core systems. Int Symp Comput Archit Digital Syst (CADS)
Farkish A, Jahanian A (2012) Parallelizing the FPGA global routing algorithm on multi-core systems without quality degradation. Inst Electr Inf Commun Eng Electron Express J 8(24):35–39
Lin M, Wawrzynek J (2010) Improving FPGA placement with dynamically adaptive stochastic tunneling. In: IEEE transaction on computer-aided design of integrated circuits and systems, vol 29, no 12, pp 1858–1869
Andrew B, Kahng J (2011) VLSI physical design, from graph partitioning to timing closure. Springer, Berlin
Tony F, Cong J, Kong T, Joseph R (2000) Multilevel optimization for large-scale circuit placement. ICCAD, Shanghai, pp 171–176
Tony F, Cong J, Joseph R, Min X (2005) mPL6: a robust multilevel mixed-size placement engine. ISPD, Madrid, pp 227–229
Areibi S, Grewal G, Banerji D, Du P (2007) Hierarchical FPGA placement. Can J Electr Comput Eng 32(1):53–64
Ababei C (2009) Speeding up FPGA placement via partitioning and multithreading. Int J Reconfigurable Comput 2009:1–9. Art ID 514754. doi:10.1155/2009/514754
Taghavi T, Yang X, Wang M, Sarrafzadeh M (2007) Dragon 2005: large scale mixed-sized placement tool. In: International symposium on physical design, ISPD design contest, pp 42–47
Jarrod A, David A, Igor L (2007): Capo: congestion-driven placement for standard-cell and RTL netlists with incremental capability. In: Modern circuit placementseries on integrated circuits and systems, pp 97–133
Vicente J, Lanchares J, Hermida R (2003) Placement by thermodynamic simulated annealing. Phys Lett A 317:415–423
Tessier R (2002) Fast placement approaches for FPGAs. ACM Trans Des Autom Electron Syst 7:284–305
Maidee P, Ababei C, Bazargan K (2003) Fast timing-driven partitioning based placement for island style FPGAs. In: Proceedings of the 40th annual design automation conference, pp 598–603
John A, Prithviraj B (1996) Parallel simulated annealing strategies for VLSI cell placement. In: VLSI design, pp 37–42
Chen H, Cheng N, MacDonald J, Suaris P, Yao B, Zhu Z (2003) Analgebraic multigrid solver for analytical placement with layout based clustering. In: Proceedings of the IEEE/ACM design automation conference, pp 794–799
Viswanathan N, Chris C (2005) FastPlace efficient analytical placement using cell shifting, iterative local refinement and a hybrid net model. IEEE Trans CAD Integr Circ Syst 24(5):722–733
Robert C, Christian F, Laura R, Gary G (2012) A formal and empirical analysis of recombination for genetic algorithm-based approaches to the FPGA placement problem. CCECE, pp 1–6
Andrzej K, Zbigniew N (2009) FPGA placement by using Hopfield neural network. J Microelectron Int 26:22–32
Betz V, Rose J (2000) VPR and T-VPack: versatile packing, placement and routing for FPGAs package. ver. 4.30
Chen G, Cong J (2005) Simultaneous timing-driven placement and duplication. In: Proceedings of the ACM/SIGDA 13th international symposium on FPGAs, Monterey, Calif., pp 51–59
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Daryanavard, H., Eshghi, M. & Jahanian, A. A fast placement algorithm for embedded just-in-time reconfigurable extensible processing platform. J Supercomput 71, 121–143 (2015). https://doi.org/10.1007/s11227-014-1290-y
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DOI: https://doi.org/10.1007/s11227-014-1290-y