A palladium-catalyzed dicarbonylation of p-benzoquinones with aryl triflates has been developed. Using Cr(CO)6 as the CO source, the reaction proceeds smoothly and efficiently to give a series of aryl esters in moderate to good yields (up to 90%).
已经开发了对苯醌与芳基三氟甲磺酸酯的钯催化二羰基化反应。使用 Cr(CO) 6作为 CO 源,该反应顺利且高效地进行,以中等至良好的收率(高达 90%)得到一系列芳基酯。
Lower bound estimation of hardware resources for scheduling in high-level synthesis
作者:Zhaoxuan Shen、Ching Chuen Jong
DOI:10.1007/bf02960762
日期:2002.11
In high-level synthesis of VLSI circuits, good lower bound prediction can efficiently narrow down the large space of possible designs. Previous approaches predict the lower bound by relaxing or even ignoring the precedence constraints of the data flow graph (DFG), and result in inaccuracy of the lower bound. The loop folding and conditional branch were also not considered. In this paper, a new stepwise refinement algorithm is proposed, which takes consideration of precedence constraints of the DFG to estimate the lower bound of hardware resources under time constraints. Processing techniques to handle multi-cycle, chaining, pipelining, as well as loop folding and mutual exclusion among conditional branches are also incorporated in the algorithm. Experimental results show that the algorithm can produce a very tight and close to optimal lower bound in reasonable computation time.
Variables bounding based retiming algorithm
作者:Zongwei Lu、Zhenghui Lin、Houpeng Chen
DOI:10.1007/bf02960770
日期:2002.11
Retiming is a technique for optimizing sequential circuits. In this paper, we discuss this problem and propose an improved retiming algorithm based on variables bounding. Through the computation of the lower and upper bounds on variables, the algorithm can significantly reduce the number of constraints and speed up the execution of retiming. Furthermore, the elements of matrixes D and W are computed in a demand-driven way, which can reduce the capacity of memory. It is shown through the experimental results on ISCAS89 benchmarks that our algorithm is very effective for large-scale sequential circuits.