Neural network models are advancing rapidly and becoming more complex. Application developers using these new models need faster AI inference but typically can’t afford more power, space, or cooling. Researchers have put forth various strategies in efforts to wring out more performance from AI inference architectures,… Read More
Area-optimized AI inference for cost-sensitive applications
Often, AI inference brings to mind more complex applications hungry for more processing power. At the other end of the spectrum, applications like home appliances and doorbell cameras can offer limited AI-enabled features but must be narrowly scoped to keep costs to a minimum. New area-optimized AI inference technology from… Read More
Ultra-efficient heterogeneous SoCs for Level 5 self-driving
The latest advanced driver-assistance systems (ADAS) like Mercedes’ Drive Pilot and Tesla’s FSD perform SAE Level 3 self-driving, with the driver ready to take back control if the vehicle calls for it. Reaching Level 5 – full, unconditional autonomy – means facing a new class of challenges unsolvable with existing technology… Read More
CEO Interview: Da Chuang of Expedera
Da is co-founder and CEO of Expedera. Previously, he was cofounder and COO of Memoir Systems, an optimized memory IP startup, leading to a successful acquisition by Cisco. At Cisco, he led the Datacenter Switch ASICs for Nexus 3/9K, MDS, CSPG products. Da brings more than 25 years of ASIC experience at Cisco, Nvidia, and Abrizio.… Read More
A Packet-Based Approach for Optimal Neural Network Acceleration
The Linley Group held its Fall Processor Conference 2021 last week. There were a number of very informative talks from various companies updating the audience on the latest research and development work happening in the industry. The presentations were categorized as per their focus, under eight different sessions. The sessions… Read More