Physical design automation of structured high-performance integrated circuits

Ward, Samuel Isaac
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During the last forty years, advancements have pushed state-of-the-art placers to impressive performance placing modern multimillion gate designs in under an hour. Wide industry adoption of the analytical framework indicates the quality of these approaches. However, modern designs present significant challenges to address the multi objective requirements for multi GHz designs. As devices continue to scale, wires become more resistive and power constraints significantly dampen performance gains, continued improvement in placement quality is necessary. Additionally, placement has become more challenging with the integration of multi-objective constraints such as routability, timing and reliability. These constraints intensify the challenge of producing quality placement solutions and must be handled carefully. Exasperating the issue, shrinking schedules and budgets are requiring increased automation by blurring the boundary between manual and automated placement. An example of this new hybrid design style is the integration of structured placement constraints within traditional ASIC style circuit structures.

Structure aware placement is a significant challenge to modern high performance physical design flows. The goal of this dissertation is to develop enhancements to state-of-the-art placement flows overcoming inadequacies for structured circuits. A key observation is that specific structures exist where modern analytical placement frameworks significantly underperform. Accurately measuring suboptimality of a particular placement solution however is very challenging. As such, this work begins by designing a series of structured placement benchmarks. Generating placement for the benchmarks manually offers the opportunity to accurately quantify placer performance. Then, the latest generation of academic placers is compared to evaluate how the placers performed for these design styles. Results of this work lead to discoveries in three key aspects of modern physical design flows.

Datapath placement is the first aspect to be examined. This work narrows the focus to specifically target datapath style circuits that contain high fanout nets. As the datapath benchmarks showed, these high fanout nets misdirect analytical placement flows. To effectively handle these circuit styles, this work proposes a new unified placement flow that simultaneously places random-logic and datapath cells. The flow is built on top of a leading academic force-directed placer and significantly improves the quality of datapath placement while leveraging the speed and flexibility of existing algorithms.

Effectively placing these circuits is not enough because in modern high performance designs, datapath circuits are often embedded within a larger ASIC style circuit and thus are unknown. As such, the next aspect of structured placement applies novel data learning techniques to train, predict, and evaluate potential structured circuits. Extracted circuits are mapped to groups that are aligned and simultaneously placed with random logic.

The third aspect that can be enhanced with improved structured placement impacts local clock tree synthesis. Performance and power requirements for multi-GHz microprocessors necessitate the use of a grid-based clock network methodology, wherein a global clock grid is overlaid on the entire die area followed by local buffered clock trees. This clock mesh methodology is driven by three key reasons: First, full trees do not offer enough performance for modern microprocessors. Second, clock trees offer significant power savings over full clock meshes. Third, local clock trees reduce the local clock wiring demands compared to full meshes at lower level metal layers. To meet these demands, a shift in latch placement methodology is proposed by using structured placement templates. Placement configurations are identified a priori with significantly lower capacitance and the solutions are developed into placement templates.

Results through careful experimentation demonstrate the effectiveness of these approaches and the impact potential for modern high-speed designs.