在以查找表(Lookup table)為基礎的可程式邏輯陣列(FPGA)架構下,我們提出一個壓縮樹合成演算法(DOCT)。此演算法的主要目的是為了達到延遲最佳化。首先,在給定查找表的輸入限制之下,此演算法會先產生一組相對應的元素樣本集合,再藉著這些元素樣本,用整數線性規劃法(ILP)去合成出延遲最佳化的壓縮樹。並且在不失去延遲最佳化的特性下,更進一步用一套後製程序去降低壓縮數所需要的面積。在實驗部分,我們把結果跟另一個演算法(GPC)做比較。結果顯示,在現今的製程技術下,我們的延遲平均降低32%,而面積平均降低21%
In this thesis, we present a compressor tree synthesis algorithm, named DOCT, which guarantees the delay optimal implementation in lookup-table (LUT) based FPGAs. Given a targeted K-input LUT architecture, DOCT firstly derives a finite set of prime patterns as essential building blocks. Then, it shows that a delay optimal compressor tree can always be constructed by those derived prime patterns via integer linear programming (ILP). Without loss of delay optimality, a post-processing procedure is invoked to reduce the number of demanded LUTs for the generated compressor tree design. DOCT has been evaluated over a broad set of benchmark circuits. Compared to the previous heuristic approach, the experimental results show that DOCT reduces the depth of the compressor tree by 32%, and the number of LUTs by 21% on average based on the modern 6-input LUT-based FPGA architecture.