2008Auerbach Publications eBooksRequires access

Timing-Driven Placement

David Z. Pan, Bill Halpin, Haoxing Ren

Open publisher page 19 citations

Abstract

This chapter reviews two basic sets of netweighting algorithms: static netweighting and dynamic netweighting. It explores two global placement approaches: partitioning and force-directed, a several detailed placement approaches. The chapter examines a mincut-based approach and two analytical partitioning-based approaches and presents several representative and techniques for Timing-driven placement (TDP) and timing-aware placement. Timing convergence metrics measure the extent to which a placement satisfies timing constraints. The most interesting aspect of the TDP is the mechanism to translate timing metrics into actions to drive the core placement engines. Netweighting-based TDP is very simple to implement and less computational intensive. Static netweighting computes the netweights once before TDP. It can be divided into two categories: empirical netweighting and sensitivity-based netweighting. Empirical netweighting assigns netweight based on the critically of the net, which indicates how much the placer should reduce the wirelength on this net.

About this research paper

What this paper is about

This chapter reviews two basic sets of netweighting algorithms: static netweighting and dynamic netweighting. It explores two global placement approaches: partitioning and force-directed, a several detailed placement approaches. The chapter examines a mincut-based approach and two analytical partitioning-based approaches and presents several representative and techniques for Timing-driven placement (TDP) and timing-aware placement. Timing convergence metrics measure the extent to which a placement satisfies timing constraints. The most interesting aspect of the TDP is the mechanism to translate timing metrics into actions to drive the core placement engines. Netweighting-based TDP is very simple to implement and less computational intensive. Static netweighting computes the netweights once before TDP. It can be divided into two categories: empirical netweighting and sensitivity-based netweighting. Empirical netweighting assigns netweight based on the critically of the net, which indicates how much the placer should reduce the wirelength on this net.

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OpenAlex reports 19 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This chapter reviews two basic sets of netweighting algorithms: static netweighting and dynamic netweighting. It explores two global placement approaches: partitioning and force-directed, a several detailed placement approaches. The chapter examines a mincut-based approach and two analytical partitioning-based approaches and presents several representative and techniques for Timing-driven placement (TDP) and timing-aware placement. Timing convergence metrics measure the extent to which a placement satisfies timing constraints. The most interesting aspect of the TDP is the mechanism to translate timing metrics into actions to drive the core placement engines. Netweighting-based TDP is very simple to implement and less computational intensive. Static netweighting computes the netweights once before TDP. It can be divided into two categories: empirical netweighting and sensitivity-based netweighting. Empirical netweighting assigns netweight based on the critically of the net, which indicates how much the placer should reduce the wirelength on this net.

Key concepts: Computer science

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