XC7K480T-2FFG1156I _AD1989BJCPZ Introduction

Xilinx's recent major developments in EDA will have a real impact on FPGA design productivity.

In the developer session specially set up at the Xilinx Adapt - China Station Online Technology Conference, Lauren Gao, a senior Xilinx software tool expert, will explain in detail all the new functions and design methods mentioned in this article.

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Therefore, the trade-off often faced in EDA is between compile time and QoR. To make matters worse, the optimization algorithm itself is polynomial and can fluctuate exponentially with the size of the design.

As we all know, problems such as Go, autonomous driving, RNA translation and transformation, and protein folding can now be solved by machine learning. Machine learning is about finding patterns in big data. Machine learning is clearly better than humans when dealing with petabytes of data.

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