scholarly journals Optimization of Physically-Aware Synthesis for Digital Implementation Flow

2018 ◽  
Vol 7 (2.11) ◽  
pp. 31 ◽  
Author(s):  
Leo E. Geralla ◽  
Melvin Joey de Guzman ◽  
Jefferson A. Hora

Synthesis is very important to have a high-quality implementation of every design. However, more accurate results could not be achieved if we will not consider the expected effects of routing delay introduced by placement and routing. This delay causes the poor timing correlation between the logical-only synthesis and Place and Route. . Now, tools with physical aware synthesis allow the user to integrate the physical information much early in the process. While such technique is readily available in the tools itself, there is no established flow to utilize the use of physical aware synthesis to the whole ASIC design process. Moreover, there’s lack of in-depth experimental analysis, specifically on commercially available designs, on the correlation of physically aware synthesis to the subsequent steps in the backend of the whole design process such as the place and route (PnR) and Timing Closure (STA). With this study, optimal flow for synthesis run is achieved through several experimental setups. Effects in place and route (PNR), and Static Timing Analysis (STA) is also observed and documented. Two different physically aware synthesis methodologies are proven to have improved timing correlation between the synthesis and PNR results. Power after signoff also improved significantly. Total runtime from synthesis to timing closure reduces because of much lesser violations in the first iteration alone.  

2020 ◽  
Vol 8 (6) ◽  
pp. 5322-5325

Metal interconnects are used to make the interconnections between different part of the circuitry to realize any System on Chip (SoC) design. For the advanced process technologies, the metal interconnects affects the performance of the design. For nanometer process technologies, the coupling effect in the interconnect causes crosstalk and noise. These noise and crosstalk must be affect the operating speed of the design. This is most responsible candidate for the timing aspect of the design. Thus, the physical design and verification of the advanced process technologies should be include the effects of noise and crosstalk. If the timing of a design is not verified, then the design may not perform at the desired operating speed. The power and area are the other factors, that also to be consider with timing for a faster design. There will always be a trade-off between these three factors. Static Timing Analysis (STA) is one of the many techniques used by the designers to verify the timing of the design and also for closing the design with respect to timing, which is called as timing closure.


2019 ◽  
Vol 13 (02) ◽  
pp. 229-244
Author(s):  
James Obert ◽  
Tom J. Mannos

To counter manufacturing irregularities and ensure ASIC design integrity, it is essential that robust design verification methods are employed. It is possible to ensure such integrity using ASIC static timing analysis (STA) and machine learning. In this research, uniquely devised machine and statistical learning methods which quantify anomalous variations in Register Transfer Level (RTL) or Graphic Design System II (GDSII) format are discussed. To measure the variations in ASIC analysis data, the timing delays in relation to path electrical characteristics are explored. It is shown that semi-supervised learning techniques are powerful tools in characterizing variations within STA path data and have much potential for identifying anomalies in ASIC RTL and GDSII design data.


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