Emulation for AI: Part One
An increasing number of AI players are building their own silicon and finding that emulation is key to overcoming the major challenges.
machine learning
Optimizing the hardware implementation of machine learning algorithms
Optimizing the way in which machine learning algorithms are implemented in hardware will be a major differentiator for SoCs, especially for edge devices.
Cutting through the AI hype with OneSpin’s Raik Brinkmann
Lauro Rizzatti gets a reality check on AI for both design tools and designs themselves from the formal verification specialist.
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.
High-resolution visual recognition needs high-performance CNNs
Quadrupling the performance of a dedicated CNN engine within an embedded vision processing core brings more complex graph processing within reach.
Introducing Doc Formal: the journey so far
Our new columnist introduces himself and traces the progress of formal verification over the last two decades. Join the discussion.
The Wally Rhines interview – Part Two: AI, automotive and security
This second part looks at Mentor's views on flow neutrality, how DRS360 was born, machine learning and the threat from embedded Trojans.
How Applied Materials and fab partners are harnessing machine learning
The equipment giant's Computational Process Control strategy takes a pragmatic approach to Industry 4.0 and is likely to influence EDA tools for incoming nodes.