Variability Analysis of On-Chip Interconnect System Using Prospective Neural Network

Author(s):  
Ajita Misra ◽  
Yash Agrawal ◽  
Vinay Palaparthy ◽  
Rutu Parekh
2020 ◽  
Vol 96 (3s) ◽  
pp. 585-588
Author(s):  
С.Е. Фролова ◽  
Е.С. Янакова

Предлагаются методы построения платформ прототипирования высокопроизводительных систем на кристалле для задач искусственного интеллекта. Изложены требования к платформам подобного класса и принципы изменения проекта СнК для имплементации в прототип. Рассматриваются методы отладки проектов на платформе прототипирования. Приведены результаты работ алгоритмов компьютерного зрения с использованием нейросетевых технологий на FPGA-прототипе семантических ядер ELcore. Methods have been proposed for building prototyping platforms for high-performance systems-on-chip for artificial intelligence tasks. The requirements for platforms of this class and the principles for changing the design of the SoC for implementation in the prototype have been described as well as methods of debugging projects on the prototyping platform. The results of the work of computer vision algorithms using neural network technologies on the FPGA prototype of the ELcore semantic cores have been presented.


Author(s):  
Jong-Moon Choi ◽  
Do-Wan Kwon ◽  
Je-Joong Woo ◽  
Eun-Je Park ◽  
Kee-Won Kwon

2009 ◽  
Vol 18 (07) ◽  
pp. 1263-1285 ◽  
Author(s):  
GUOQING CHEN ◽  
EBY G. FRIEDMAN

With higher operating frequencies, transmission lines are required to model global on-chip interconnects. In this paper, an accurate and efficient solution for the transient response at the far end of a transmission line based on a direct pole extraction of the system is proposed. Closed form expressions of the poles are developed for two special interconnect systems: an RC interconnect and an RLC interconnect with zero driver resistance. By performing a system conversion, the poles of an interconnect system with general circuit parameters are solved. The Newton–Raphson method is used to further improve the accuracy of the poles. Based on these poles, closed form expressions for the step and ramp response are determined. Higher accuracy can be obtained with additional pairs of poles. The computational complexity of the model is proportional to the number of pole pairs. With two pairs of poles, the average error of the 50% delay is 1% as compared with Spectre simulations. With ten pairs of poles, the average error of the 10%-to-90% rise time and the overshoots is 2% and 1.9%, respectively. Frequency dependent effects are also successfully included in the proposed method and excellent match is observed between the proposed model and Spectre simulations.


ACS Nano ◽  
2021 ◽  
Author(s):  
Calvin Brown ◽  
Artem Goncharov ◽  
Zachary S. Ballard ◽  
Mason Fordham ◽  
Ashley Clemens ◽  
...  
Keyword(s):  

1991 ◽  
pp. 387-395d
Author(s):  
Shawn P. Day ◽  
Daniel S. Camporese
Keyword(s):  

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