Efficient use of large don't cares in high-level and logic synthesis

Author(s):  
R.A. Bergamaschi ◽  
D. Brand ◽  
L. Stok ◽  
M. Berkelaar ◽  
S. Prakash
1989 ◽  
Author(s):  
Srinivas Devadas ◽  
Hi-Keung T. Ma ◽  
A. R. Newton

VLSI Design ◽  
1995 ◽  
Vol 3 (3-4) ◽  
pp. 301-313 ◽  
Author(s):  
Marek A. Perkowski ◽  
Malgorzata Chrzanowska-Jeske ◽  
Andisheh Sarabi ◽  
Ingo Schäfer

This paper introduces several new families of decision diagrams for multi-output Boolean functions. The introduced families include several diagrams known from literature (BDDs, FDDs) as subsets. Due to this property, these diagrams can provide a more compact representation of functions than either of the two decision diagrams. Kronecker Decision Diagrams (KDDs) with negated edges are based on three orthogonal expansions (Shannon, Positive Davio, Negative Davio) and are created here for incompletely specified Boolean functions as well. An improved efficient algorithm for the construction of KDD is presented and applied in a mapping program to ATMEL 6000 fine-grain FPGAs. Four other new families of functional decision diagrams are also presented: Pseudo KDDs, Free KDDs, Boolean Ternary DDs, and Boolean Kronecker Ternary DDs. The last two families introduce nodes with three edges and require AND, OR and EXOR gates for circuit realization. There are two variants of each of the last two families: canonical and non-canonical. While the canonical diagrams can be used as efficient general-purpose Boolean function representations, the non-canonical variants are also applicable to incompletely specified functions and create don't cares in the process of the creation of the diagram.. They lead to even more compact circuits in logic synthesis and technology mapping.


1990 ◽  
Vol 1 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Srinivas Devadas ◽  
Hi-Keung Tony Ma ◽  
A. Richard Newton

2013 ◽  
Vol 22 (04) ◽  
pp. 1350025
Author(s):  
STAVROS P. DOKOUZYANNIS ◽  
ARGIRIS P. MOKIOS

This paper analyzes the design automation of embedded Systolic Array Processors (SAPs), into large scale Field Programmable Gate Array (FPGA) devices. SAPs are hardware implementations of a class of iterative, high-level language algorithms, for applications where the high-speed of processing has the principal meaning of a design. Embedding SAPs onto FPGAs is a complex process. The optimization phase in this process reduces the SAP significantly, thus less FPGA area is occupied by the embedded design, without any loss in the final performance. The present paper examines the effect of Projection Vectors (PVs) and Task Scheduling Vectors (TSVs) on the optimization process. Two optimization approaches are examined, namely technology mapping using FlowMap and Flowpack algorithms and optimization via logic synthesis using Xilinx Synthesis Tool. The multiplication of matrices, with entries being up to 32-bit integer vectors, has been taken as a sample space for the experiments conducted. The results, confirm that the selection of PV and TSV greatly affects the number of input/output signal connections of the FPGA, while the selection of an optimization approach affects the final number of logic resources occupied on the targeted device.


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