TCP-Net is Test Case Prioritization using End-to-End Deep Neural Networks and addresses the challenges of today's software-rich projects.
The computational and algorithmic demands made by computer vision systems highlight HLS' value for AI system development.
The second part of this feature looks at how Wave Computing's objectives with its dataflow processing unit for AI mapped to the use of emulation in its development.
An increasing number of AI players are building their own silicon and finding that emulation is key to overcoming the major challenges.
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?
Lauro Rizzatti gets a reality check on AI for both design tools and designs themselves from the formal verification specialist.
High-performance vision-processing algorithms need optimized CNN engines to deliver the right performance within the power budget of embedded applications.
In both data centers and automobiles deep learning is taking hold. But it is a technique that challenges conventional microprocessors, leading system designers to look at alternative architectures for acceleration.
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