High-level synthesis for AI: Part One
The computational and algorithmic demands made by computer vision systems highlight HLS' value for AI system development.
Expert Insights
Enabling the move to a system-centric view
Bob Smith of the ESD Alliance describes how we can promote the ongoing evolution of the design ecosystem.
Understanding USB 3.2 and Type-C
The basics of USB 3.2, how to implement it in an SoC, and how USB Type-C connectors and cables are used in USB 3.2 systems.
Why AI needs security
As AI becomes pervasive in computing applications, so too does the need for high-grade security in all levels of the system.
Flexible embedded vision processing architectures for machine-learning applications
Machine-learning strategies for embedded vision are evolving so quickly that designers need access to flexible, heterogenous processor architectures that can adapt as the algorithms evolve.
Managing waivers in reliability verification
Dina Medhat describes what you need to know about the types of waiver strategy that can be applied.
Picking the right-sized crypto processor for your SoC
Choosing the right crypto processor implementation involves a complex set of design tradeoffs between speed, area, power consumption and flexibility. Using consistent benchmarks can help explore your options.
The impact of AI on autonomous vehicles
Many car manufacturers are exploring the possibilities of autonomous vehicles. But what will it take to build sufficient AI performance into them to enable true autonomy?
How eFPGAs will help build the brave new world of AI
Artificial intelligence and machine learning require the performance and flexibility offered by embedded FPGA (eFPGA) technology.
Optimizing power and performance trade-offs in CNN implementations for embedded vision
High-performance vision-processing algorithms need optimized CNN engines to deliver the right performance within the power budget of embedded applications.
PLATINUM SPONSORS
View All Sponsors