An Island-Based GA Implementation for VLSI Standard-Cell Placement

نویسندگان

  • Guangfa Lu
  • Shawki Areibi
چکیده

Genetic algorithms require relatively large computation time to solve optimization problems, especially in VLSI CAD such as module placement. Therefore, island-based parallel GAs are used to speed up this procedure. The migration schemes that most researchers proposed in the past have migration near or after the demes converged [1,2]. However, for the placement of medium or large standard-cell circuits, the time required for convergence is extremely long, which makes the above migration schemes non practical. In this paper, we propose a novel migration scheme for synchronous island-based GA. Compared to the widely used ring topology that usually produces worse solutions at the beginning of the search but better solutions at later generations, the proposed migration scheme enables a parallel GA to outperform its serial version most of the time. Near linear speedup is obtained. We also implemented an asynchronous model that can achieve super-linear speedup.

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

An Improved Standard Cell Placement Methodology using Hybrid Analytic and Heuristic Techniques

In recent years, size of VLSI circuits is dramatically grown and layout generation of current circuits has become a dominant task in design flow. Standard cell placement is an effective stage of physical design and quality of placement affects directly on the performance, power consumption and signal immunity of design. Placement can be performed analytically or heuristically. Analytical placer...

متن کامل

A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement

In this paper, we present a parallel tabu search (TS) algorithm for efficient optimization of a constrained multiobjective VLSI standard cell placement problem. The primary purpose is to accelerate TS algorithm to reach near optimal placement solutions for large circuits. The proposed technique employs a candidate list partitioning strategy based on distribution of mutually disjoint set of move...

متن کامل

Parallel Evolutionary Algorithms for Multiobjective Placement Problem

Non-deterministic iterative heuristics such as Tabu Search (TS), Simulated Evolution (SimE), Simulated Annealing (SA), and Genetic Algorithms (GA) are being widely adopted to solve a range of hard optimization problems [1]. This interest is attributed to their generality, ease of implementation, and their ability to deliver high quality results. However, depending on the size of the problem, su...

متن کامل

Performance Evaluation and Comparison of GA, SA & LSA Based Algorithms for Standard Cell Placement in VLSI Design

Performance Evaluation and Comparison of GA, SA & LSA Based Algorithms for Standard Cell Placement in VLSI Design Dr. Aaquil Bunglowala, Dr. Nidhi Asthana Department of Electronics and Telecommunication Department of Engineering Mathematics MPSTME, Shirpur Campus,Maharashtra, SAIT,Indore, M.P. INDIA __________________________________________________________________________________________ Abstr...

متن کامل

Accelerating Multiobjective Vlsi Cell Placement with Parallel Evolutionary/tabu Search Heuristics

Multiobjective combinatorial optimization problems in various disciplines remain to be the focus of extensive research due to their inherent hard nature and difficulty of finding near-optimal solutions. Iterative heuristics like Tabu Search (TS) and Simulated Evolution (SimE) have successfully been employed to solve a range of such optimization problems [1]. These heuristics are able to obtain ...

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 2004