As AI & ML chips proliferate, the focus is moving to deployment and practical applications. This change brings a corresponding shift in the technical problems chip makers and their customers need to solve. Do the devices perform as expected under real-world conditions? What support do software development teams – both at the IC maker and systems integrator – require? Can devices adapt as software loads change and the devices themselves are subject to aging effects?
The pioneers of the current generation of AI and machine learning devices faced a fundamental problem: how to build architectures incorporating many, many processing nodes, that deal with often sparse data sets and deliver results while achieving any level of resource efficiency.
The world has moved on, and today’s AI/ML chips now deal efficiently with their target workloads. But echoes of the early efficiency and performance problems remain. Chip and system performance metrics are often dominated by infrequently occurring long-tail phenomena which may not show up at first sight as bugs. Interactions between on-chip hardware blocks are not predictable – at least in the sense that traditional designers understand. Hardware and software need to be designed and optimized in parallel. The sheer size and complexity of many of these new devices makes it impossible to simulate or emulate every aspect of their performance before tape-out – and in the case of real-time and cyberphysical systems, to predict every possible interaction with the real world.
This panel-style discussion will address these issues from a number of standpoints:
- What are the main deployment challenges at the technical level?
- What is required from this new generation of chips to allow them to be integrated successfully into target systems?
- Looking beyond systems integration, what are the requirements when the chips are deployed in the field?
- How can IC design teams ensure their chips attain maximum performance?
- What tools and methodologies are available to support them?
Siemens
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Siemens Digital Industries Factory Automation is an innovation and technology leader in industrial automation and digitalization. In close cooperation with our partners and customers, we are the driving force for the digital transformation in the discrete and process industries and integrate cutting-edge technologies such as artificial intelligence, edge computing, industrial 5G, autonomous handling systems, blockchain and additive manufacturing into our Digital Enterprise portfolio. Taking advantage of our experts on cutting-edge technologies as well as our deep knowledge and understanding of the challenges within the industry, we provide our customers with solutions which bring tangible value.