Dealing with the over-pessimism in ASIC physical design flow

Author(s):  
R. Iqbal
Keyword(s):  
2021 ◽  
Vol 26 (5) ◽  
pp. 1-25
Author(s):  
Heechun Park ◽  
Bon Woong Ku ◽  
Kyungwook Chang ◽  
Da Eun Shim ◽  
Sung Kyu Lim

Studies have shown that monolithic 3D ( M3D ) ICs outperform the existing through-silicon-via ( TSV ) -based 3D ICs in terms of power, performance, and area ( PPA ) metrics, primarily due to the orders of magnitude denser vertical interconnections offered by the nano-scale monolithic inter-tier vias. In order to facilitate faster industry adoption of the M3D technologies, physical design tools and methodologies are essential. Recent academic efforts in developing an EDA algorithm for 3D ICs, mainly targeting placement using TSVs, are inadequate to provide commercial-quality GDS layouts. Lately, pseudo-3D approaches have been devised, which utilize commercial 2D IC EDA engines with tricks that help them operate as an efficient 3D IC CAD tool. In this article, we provide thorough discussions and fair comparisons (both qualitative and quantitative) of the state-of-the-art pseudo-3D design flows, with analysis of limitations in each design flow and solutions to improve their PPA metrics. Moreover, we suggest a hybrid pseudo-3D design flow that achieves both benefits. Our enhancements and the inter-mixed design flow, provide up to an additional 26% wirelength, 10% power consumption, and 23% of power-delay-product improvements.


2019 ◽  
pp. 81-114
Author(s):  
Yu‐Shiang Lin ◽  
Sandeep K. Goel ◽  
Jonathan Yuan ◽  
Tom Chen ◽  
Frank Lee
Keyword(s):  

Author(s):  
Huanyu Wang ◽  
Qihang Shi ◽  
Adib Nahiyan ◽  
Domenic Forte ◽  
Mark M. Tehranipoor

2013 ◽  
Vol 12 (10) ◽  
pp. 3239-3264 ◽  
Author(s):  
Maryam Yazdani ◽  
Morteza Saheb Zamani ◽  
Mehdi Sedighi

Nowadays in VLSI number of transistors integrated on a single silicon chip is increasing day by day and the complexity of the design is increases tremendously. This makes very difficult for the designer and EDA tools. As number of instances increases the run time and memory for implementing the design increases. This will make more pressure on the designer because if product is not completed within the time to market company will lost so much of money. Floorplanning is the basic building step for any hierarchical physical design flow. Floorplanning is taking more amount of time in entire design hierarchical flow. If floorplanning is not good the entire design will take more time and it will increase a greater number of iterations to complete the design. In the top-level chip planning the quality of the floorplanning depends on the proper alignment of blocks and easy to meet the timing and congestion. To reduce memory size of CPU and run time, in this project we are using a method of Backbox model based top level hierarchical floorplanning based physical design. The main aim of this project is to reduce the number of instances which are not necessary in the top level chip floor planning which reduces peak memory for the design and also reducing CPU run time for getting proper prototype design in the top level ASIC design and estimate the congestion in the design at initial stage and modify floor planning to obtain quality of prototype model in the floorplanning. This project is designed on cadence encounter tool.


Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1995
Author(s):  
Pingakshya Goswami ◽  
Dinesh Bhatia

Design closure in general VLSI physical design flows and FPGA physical design flows is an important and time-consuming problem. Routing itself can consume as much as 70% of the total design time. Accurate congestion estimation during the early stages of the design flow can help alleviate last-minute routing-related surprises. This paper has described a methodology for a post-placement, machine learning-based routing congestion prediction model for FPGAs. Routing congestion is modeled as a regression problem. We have described the methods for generating training data, feature extractions, training, regression models, validation, and deployment approaches. We have tested our prediction model by using ISPD 2016 FPGA benchmarks. Our prediction method reports a very accurate localized congestion value in each channel around a configurable logic block (CLB). The localized congestion is predicted in both vertical and horizontal directions. We demonstrate the effectiveness of our model on completely unseen designs that are not initially part of the training data set. The generated results show significant improvement in terms of accuracy measured as mean absolute error and prediction time when compared against the latest state-of-the-art works.


Integration ◽  
2018 ◽  
Vol 63 ◽  
pp. 18-30 ◽  
Author(s):  
Vlastimil Kote ◽  
Adam Kubacak ◽  
Patrik Vacula ◽  
Jiri Jakovenko ◽  
Miroslav Husak

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