Excerpt from article: “AI and ML fuel Catapult and Calibre updates“
Catapult HLS AI
As more processing necessarily moves away from the cloud, an increasing challenge for edge ML silicon is balancing requirements for power, performance and area (PPA). This is leading an increasing number of players to opt for custom or semi-custom or custom convolutional neural network (CNN) architectures over off-the-shelf silicon.
HLS has already been used across a number of AI designs (the first of our two-part series on the topic can be found here). The new Catapult tookit leverages this experience across a range of features including reference designs with four starter kits for AI/Vision, an FPGA demonstrator, CPU subsystem, HW/SW interface, and HLS accelerator.
The tookit designs are:
-Edge detection from HOG line-buffer architecture.
-2D convulution engine reconfigurable processing element (PE) array.
-Nine-layer CNN full custom fused architecture.
-Nine-layer CNN reconfigurable Eyeriss PE array.
Read the entire article on TechDesignForum originally published on May 23rd, 2019.