This presentation will look at how best to optimize embedded FPGA technology for integration in SoCs that are used in emerging, high-performance and compute intensive applications like artificial intelligence, machine learning, 5G wireless, and ADAS or autonomous driving vehicles. Beyond choosing the optimal mix of logic, memory and DSP resources, customers can also add custom blocks that are optimized for their end application that offer much higher performance and a significant reduction in the eFPGA die size, which in-turn reduces silicon costs and power consumption.