Sample Method for Minimization of OBDDs

نویسندگان

  • Anna Slobodová
  • Christoph Meinel
چکیده

This paper contributes to the solution of the minimization problem of Ordered Binary Decision Diagrams by means of variable reordering. We suggest a new heuristic that is based on sampling. A small OBDD sample is chosen from the OBDDs that are considered for minimization. Solving the problem for this small sample, we obtain a variable order that is adapt for the entire OBDDs. We present rst experimental results with the Sample Reordering targeted at combinatorial veriication. The suggested heuristic is substantially faster than Sifting.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Exact Minimization of Free BDDs and Its Application to Pass-Transistor Logic Optimization

In several design methods for Pass-transistor Logic (PTL) circuits, Boolean functions are expressed as OBDDs in decomposed form and then the component OBDDs are directly mapped to PTL cells. The total size of OBDDs (number of nodes) corresponds to the circuit size. In this paper, we investigate a method for PTL synthesis based on exact minimization of Free BDDs (FBDDs). FBDDs are well-studied e...

متن کامل

Dynamic minimization of OKFDDs

We present methods for the construction of small Ordered Kronecker Functional Decision Diagrams (OKFDDs). OKFDDs are a generalization of Ordered Binary Decision Diagrams (OBDDs) and Ordered Functional Decision Diagrams (OFDDs) as well. Our approach is based on dynamic variable ordering and decomposition type choice. For changing the decomposition type we use a new method. We brieey discuss the ...

متن کامل

Learning Heuristics for Obdd Minimization by Evolutionary Algorithms Learning Heuristics for Obdd Minimization by Evolutionary Algorithms

Ordered Binary Decision Diagrams (OBDDs) are the state-of-the-art data structure in CAD for ICs. OBDDs are very sensitive to the chosen variable ordering, i.e. the size may vary from linear to exponential. In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics for OBDD minimization starting from a given set of basic operations. The diierence to other previous approa...

متن کامل

Frankfurt am Main , March 1995 Dynamic Minimization of OKFDDs

We present methods for the construction of small Ordered Kronecker Functional Decision Diagrams (OKFDDs). OKFDDs are a generalization of Ordered Binary Decision Diagrams (OBDDs) and Ordered Functional Decision Diagrams (OFDDs) as well. Our approach is based on dynamic variable ordering and decomposition type choice. For changing the decomposition type we use a new more eecient method. The quali...

متن کامل

Learning Heuristics for OBDD Minimization by Evolutionary Algorithms

Ordered Binary Decision Diagrams (OBDDs) are the state-of-the-art data structure in CAD for ICs. OBDDs are very sensitive to the chosen variable ordering, i.e. the size may vary from linear to exponential. In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics for OBDD minimization starting from a given set of basic operations. The diierence to other previous approa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1998