For compute-intensive applications like 5G cellular and machine learning DNN/CNN, Xilinx’s new vector processor AI Engines are an array of VLIW SIMD high-performance processors that deliver up to 8X silicon compute density at 50% the power consumption of traditional programmable logic solutions.
This white paper explores the architecture, applications, and benefits of using Xilinx’s new AI Engine for compute intensive applications like 5G cellular and machine learning DNN/CNN.
5G requires between five to 10 times higher compute density when compared with prior generations; AI Engines have been optimized for DSP, meeting both the throughput and compute requirements to deliver the high bandwidth and accelerated speed required for wireless connectivity.
The emergence of machine learning in many products, often as DNN/CNN networks, dramatically increases the compute-density requirements. AI Engines, which are optimized for linear algebra, provide the compute density to meet these demands — while also reducing the power consumption by as much as 50% when compared to similar functions being performed in programmable logic.
AI Engines are programmed using a C/C++ paradigm familiar to many programmers. AI Engines are integrated with Xilinx’s Adaptable And Scalar Engines to provide a highly flexibly and capable overall solution.
Click here to read more.
 |
 |
 |
 |
 |
 |
Leave a Reply