David A. Papa

Unification of partitioning, placement and floorplanning

Large macro blocks, pre-designed datapaths, embedded memories and analog blocks are increasingly used in ASIC designs. However, robust algorithms for large-scale placement of such designs have only recently been considered in the literature, and improvements by over 10% per paper are still common. Large macros can be handled by traditional floorplanning, but are harder to account for in min-cut and analytical placement. On the other hand, traditional floorplanning techniques do not scale to large numbers of objects, especially in terms of solution quality. We propose to integrate min-cut placement with fixed-outline floor-planning to solve the more general placement problem, which includes cell placement, floorplanning, mixed-size placement and achieving routability. At every step of min-cut placement, either partitioning or wirelength-driven, fixed-outline floorplanning is invoked. If the latter fails, we undo an earlier partitioning decision, merge adjacent placement regions and re-floorplan the larger region to find a legal placement for the macros. Empirically, this framework improves the scalability and quality of results for traditional wirelength-driven floorplanning. It has been validated on recent designs with embedded memories and accounts for routability. Additionally, we propose that free-shape rectilinear floorplanning can be used with rough module-area estimates before synthesis.

Capo: robust and scalable open-source min-cut floorplacer

In this invited note we describe Capo, an open-source software tool for cell placement, mixed-size placement and floorplanning with emphasis on routability. Capo is among the fastest academic placers and scales to millions of movable objects. This note surveys the overall structure of Capo, discusses recent improvements and describes ongoing research.

Min-cut floorplacement

Large macro blocks, predesigned datapaths, embedded memories, and analog blocks are increasingly used in application-specific integrated circuit (ASIC) designs. However, robust algorithms for large-scale placement of such designs have only recently been considered in the literature. Large macros can be handled by traditional floorplanning, but are harder to account for in min-cut and analytical placement. On the other hand, traditional floorplanning techniques do not scale to large numbers of objects, especially in terms of solution quality. The authors propose to integrate min-cut placement with fixed-outline floorplanning to solve the more general placement problem, which includes cell placement, floorplanning, mixed-size placement, and achieving routability. At every step of min-cut placement, either partitioning or wirelength-driven fixed-outline floorplanning is invoked. If the latter fails, the authors undo an earlier partitioning decision, merge adjacent placement regions, and refloorplan the larger region to find a legal placement for the macros. Empirically, this framework improves the scalability and quality of results for traditional wirelength-driven floorplanning. It has been validated on recent designs with embedded memories and accounts for routability. Additionally, the authors propose that free-shape rectilinear floorplanning can be used with rough module-area estimates before logic synthesis

RUMBLE: an incremental, timing-driven, physical-synthesis optimization algorithm

Physical-synthesis tools are responsible for achieving timing closure. Starting with 130-nm designs, multiple cycles are required to cross the chip, making latch placement critical to success. We present a new physical-synthesis optimization for latch placement called Rip Up and Move Boxes with Linear Evaluation (RUMBLE) that uses a linear timing model to optimize timing by simultaneously replacing multiple gates. RUMBLE runs incrementally and in conjunction with static timing analysis to improve the timing for critical paths that have already been optimized by placement, gate sizing, and buffering. Experimental results validate the effectiveness of the approach: Our techniques improve slack by 41.3% of cycle time on average for a large commercial ASIC design.

Satisfying whitespace requirements in top-down placement

In this invited note we outline several algorithms and features appearing in Capo 10, free open-source software for congestion-driven standard cell placement, mixed-size placement and floorplanning. Capo scales on par with industry placers and has been successfully used with a broad range of netlists. It can also satisfy lower bounds on local whitespace, using several techniques for global, detail and macro placement.

Physical Synthesis with Clock-Network Optimization for Large Systems on Chips

In traditional physical-synthesis methodologies, the placement of flip-flops and latches is problematic, especially for large systems on chips. A next-generation electronic-design-automation methodology improves timing closure through clock-network synthesis and placement of flip-flops and latches to avoid timing disruptions or immediately recover from them. When evaluated on large CPU designs, the methodology saw double-digit improvements in timing, wirelength, and area versus current technology.

RUMBLE: An Incremental Timing-Driven Physical-Synthesis Optimization Algorithm

Physical-synthesis tools are responsible for achieving timing closure. Starting with 130-nm designs, multiple cycles are required to cross the chip, making latch placement critical to success. We present a new physical-synthesis optimization for latch placement called Rip Up and Move Boxes with Linear Evaluation (RUMBLE) that uses a linear timing model to optimize timing by simultaneously replacing multiple gates. RUMBLE runs incrementally and in conjunction with static timing analysis to improve the timing for critical paths that have already been optimized by placement, gate sizing, and buffering. Experimental results validate the effectiveness of the approach: Our techniques improve slack by 41.3% of cycle time on average for a large commercial ASIC design.

Early research experience with OpenAccess gear: an open source development environment for physical design

Physical design EDA research in academia has historically been based on infrastructure developed independently by individual contributors. This has led to fragmentation in the community, where interaction, data interchange and comparison of results between tools are difficult. We discuss our early experience with the OpenAccess Gear system, an open source software initiative intended to provide pieces of the critical integration and analysis infrastructure that are taken for granted in proprietary tools, but often wholly absent in research tools. Built on top of the widely available OpenAccess database, OA Gear provides components such as industrial-strength static timing analysis and extensible layout and netlist visualization. We discuss preliminary results from two on-going research efforts that have adopted OA Gear as their infrastructure: retrofitting the University of Michigan Capo placer into this environment, and the addition of a timing-driven capability to the Carnegie Mellon Warp placer.

Path smoothing via discrete optimization

A fundamental problem in timing-driven physical synthesis is the reduction of critical paths in a design. In this work, we propose a powerful new technique that moves (and can also resize) multiple cells simultaneously to smooth critical paths, thereby reducing delay and improving worst negative slack or a figure-of-merit. Our approach offers several key advantages over previous formulations, including the accurate modeling of objectives and constraints in the true timing model, and a guarantee of legality for all cell locations.

Quantifying academic placer performance on custom designs

There have been significant prior efforts to quantify performance of academic placement algorithms, primarily by creating artificial test cases that attempt to mimic real designs, such as the PEKO benchmark containing known optimas [5]. The idea was to create benchmarks with a known optimal solution and then measure how far existing placers were from the known optimal. Since the benchmarks do not necessarily correspond to properties of real VLSI netlists, the conclusions were met with some skepticism. This work presents two custom constructed datapath designs that perform common logic functions with hand-designed layouts for each. The new generation of academic placers is then compared against them to see how the placers performed for these design styles. Experiments show that all academic placers have wirelengths significantly greater then the manual solution; solutions range from 1.75 to 4.88 times greater wirelengths. These testcases will be released publically to stimulate research into automatically solving structured datapath placement problems.