Excerpt from article: “Priorities Shift In IC Design”
The rush to the edge and new applications around AI are causing a shift in design strategies toward the highest performance per watt, rather than the highest performance or lowest power.
This may sound like hair-splitting, but it has set a scramble in motion around how to process more data more quickly without just relying on faster processors and accelerators. Several factors are driving these changes, including the slowdown in Moore’s Law, which limits the number of traditional options, the rollout of AI everywhere, and a surge in data from more sensors, cameras and images with higher resolutions. In addition, more data is being run though convolutional neural networks or deep learning inferencing systems, which bring huge data processing loads.
“As semiconductor scaling slows, but processing demands increase, designers are going to need to start working harder for those performance and efficiency gains,” said Russell Klein, HLS platform director at Siemens EDA. “When optimizing any system, you need to focus on the biggest inefficiencies first. For data processing on embedded systems, that will usually be software.”
Read the entire article on SemiEngineering originally published on January 16th, 2020.