Using HLS to Accelerate Computer Vision for Autonomous Drive
The algorithms to teach a computer to see, understand and make decisions for ADAS and Autonomous Drive systems require a significant amount of parallel compute performance executing at the lowest possible power. This video will introduce of why HLS (High-level Synthesis) is such a good fit for computer vision and deep learning and how it can be used adapt rapidly changing algorithms and/or trained neural networks to low-power, high performance custom hardware accelerators.
발표자 소개
Ellie Burns
Former Director of Marketing
Ms. Burns has over 30 years of experience in the chip design and the EDA industries in various roles of engineering, applications engineering, technical marketing and product management. She was formerly the Director of Marketing for the Calypto Systems' Division at Siemens EDA responsible for low-power RTL solutions with PowerPro and HLS Solutions with Catapult. Prior to Siemens and Mentor, Ms. Burns held engineering and marketing positions at CoWare, Cadence, Synopsys, Viewlogic, Computervision and Intel. She holds a BSCpE from Oregon State University.
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