Things to watch out for in tuning circuits for specific applications.
Using a device’s body bias effect allows designers to tune a circuit’s behavior to meet both power and performance specifications, but getting it right isn’t always easy. Accurate, fast, automated body bias verification is critical to ensure today’s complex designs meet demanding performance, reliability, and power usage specifications.
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Interest in the open-source ISA marks a significant shift among chipmakers, but it will require continued industry support to be successful.
Slowdown due to impact on timing, and dependencies between power, thermal and timing that may not be caught by signoff tools.
Access to source code makes it attractive for custom applications, but gaps remain in the tool flow and in software.
SoC bandwidth, integration expand as data centers use more FPGAs for machine learning.
Problems won’t derail next-gen litho, but could limit use and affect schedules.
Interest in the open-source ISA marks a significant shift among chipmakers, but it will require continued industry support to be successful.
Using the Von Neumann architecture for artificial intelligence applications is inefficient. What will replace it?
Assessing the reliability of a device requires adding more physical factors into the analysis, many of which are interconnected in complex ways.
Slowdown due to impact on timing, and dependencies between power, thermal and timing that may not be caught by signoff tools.
Improvements in power, performance and area are much more difficult to achieve, but solutions are coming into focus.
Shift to cloud model has kept power consumption in check, but that benefit may have run its course.
Old solutions don’t necessarily work anymore, particularly at advanced nodes and ultra-low voltage.
The number of critical design metrics is expanding, but the industry still grapples with their implications.
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