Using ML In EDA


Machine learning is becoming essential for designing chips due to the growing volume of data stemming from increasing density and complexity. Nick Ni, director of product marketing for AI at Xilinx, examines why machine learning is gaining traction at advanced nodes, where it’s being used today and how it will be used in the future, how quality of results compare with and without ML, and what... » read more

What’s Changing In DRAM


Most of the attention in chip scaling has been focused on logic and on-chip memory, but off-chip memory is starting to encounter problems, as well. David Fried, vice president of computational products at Lam Research, looks at the impact of shrinking features and increasing density, including variation, thermal effects and aging, as well as effects such as micro-loading and DRAM stacking. » read more

Working With RISC-V


RISC-V is coming on strong, but working with this open-source processor core isn't as simple as plugging in a commercial piece of IP. Zdenek Prikryl, CTO at Codasip, talks about utilizing hypervisors and open source tools and extensions to the RISC-V instruction set architecture, where design teams can run into problems, what will change as the architecture becomes more mature, the difference b... » read more

Changes In Auto Architectures


Automotive architectures are changing from a driver-centric model to one where technology supplements and in some cases replaces the driver. Hans Adlkofer, senior vice president and head of the Automotive Systems Group at Infineon, looks at the different levels of automation in a vehicle, what’s involved in the shift from domain to zonal architectures, why a mix of processors will be required... » read more

Sensor Fusion Everywhere


How do you distinguish between background noise and the sound of an intruder breaking glass? David Jones, head of marketing and business development for intuitive sensing solutions at Infineon, looks at what types of sensors are being developed, what happens when different sensors are combined, what those sensors are being used for today, and what they will be used for in the future. » read more

Safe And Robust Machine Learning


Deploying machine learning in the real world is a lot different than developing and testing it in a lab. Quenton Hall, AI systems architect at Xilinx, examines security implications on both the inferencing and training side, the potential for disruptions to accuracy, and how accessible these models and algorithms will be when they are used at the edge and in the cloud. This involves everything ... » read more

Design For Test Data


As design pushes deeper into data-driven architectures, so does test. Geir Eide, director for product management of DFT and Tessent Silicon Lifecycle Solutions at Siemens Digital Industries Software, talks with Semiconductor Engineering about a subtle but significant shift for designing testability into chips so that test data can be used at multiple stages during a device’s lifetime. » read more

Dynamically Reconfiguring Logic


Dynamic reconfiguration of semiconductor logic has been possible for years, but it never caught on commercially. Cheng Wang, co-founder and senior vice president of software and engineering at Flex Logix, explains why this capability has been so difficult to utilize, what’s changed, how a soft logic layer can be used to control when to read, compute, steer, and write data back to memory, and ... » read more

Problems In The Power Grid


The gap is widening between power availability and peak demand. Ritesh Tyagi, head of innovation and growth strategy at Infineon Technologies, talks about what needs to be done to fix the power grid, particularly as more cars are electrified and more electronic devices are mobile. While there currently is a surplus in power being generated on a macro level in the United States, for example, it�... » read more

Improving Power & Performance Beyond Scaling


Steven Woo, Rambus fellow and distinguished inventor, discusses architectural changes inside of servers and data centers to allow pooling of resources such as memory. That has a big impact on power efficiency and overall performance, but it also allows data centers to customize their architectures and prioritized resources with much more granularity than they can do today. » read more

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