What happens when you use DRAM at extremely low temperatures?
Rambus Chief Scientist Craig Hampel talks with Semiconductor Engineering about quantum computing and the power/performance benefits of running DRAM at extremely low temperatures.
Chips will cost more to design and manufacture even without pushing to the latest node, but that’s not the whole story.
Semiconductor devices face many hazards before and after manufacturing that can cause them to fail prematurely.
Technology adds more granularity, but starting point for design shifts as architectures cope with greater volumes of data.
Different perspectives and needs create friction as more advanced electronics are added into vehicles.
Bulk CMOS, FD-SOI and finFETs all on tap as big players vie for differentiation. But where will chipmakers go after 28nm?
AI-enabled systems are being designed to process more data locally as device scaling benefits decline.
Interest in the open-source ISA marks a significant shift among chipmakers, but it will require continued industry support to be successful.
Foundry forms ASIC subsidiary as it focuses on 14nm/12nm and above.
Market overcrowding, more efficient manufacturing, and growing list of scaling issues create a challenging competitive landscape.
Chips will cost more to design and manufacture even without pushing to the latest node, but that’s not the whole story.
Using the Von Neumann architecture for artificial intelligence applications is inefficient. What will replace it?
At least 5 technologies are in the running, with 3D XPoint leading the pack.
Slowdown due to impact on timing, and dependencies between power, thermal and timing that may not be caught by signoff tools.
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Big thank you for this interview, Ed. When I first heard about this, I found it counter-intuitive. Surely electrons would slow down. How could it work? Loved the interview and your questions. Very “cool” stuff in more ways than K.