• Chip Proposals Seek to Revive US Manufacturing - US Congress proposes aid to advance US semiconductor industry.
• CCC Report on Embedded Security Research - Conclusions of Computing Community Consortium Workshop on Embedded Security in Connected Devices.
• DARPA Kicks Off Program in Quantum Computing - University-industry teams will investigate hybrid classical-quantum optimization algorithms.
• RAND Study Advocates Post-Quantum Cryptography - New report proposes development of communication security protocols that are more resistant against future quantum computers.
• Silicon Spin Qubits Demonstrated - Researchers fabricate silicon quantum dots that can operate at temperatures above 1 K.
• DoE issues report on AI for Science - Argonne National Laboratory summarizes town hall meetings on AI, big data, and high performance computing in the next decade.
• Roadmap for Wide Bandgap Semiconductors - IEEE Power Electronics Society releases Roadmap on development of ICs of GaN and SiC for high-power applications.
• New faster parallel optimization algorithm implemented on FPGAs and GPUs - Toshiba sees applications to financial engineering.
• New project on DNA-based memory technology - Collaboration between Georgia Tech, Microsoft, University of Washington, and others.

IRDS™ Roadmap Chapter on Cryogenic Electronics and Quantum Information Processing (CEQIP)

The 2020 IRDS™ Roadmap includes a chapter on CEQIP chaired by Dr. Scott Holmes of Booz-Allen, IARPA, and the IEEE Council on Superconductivity.

This chapter describes several developing technologies, which do not yet have many mature products.

These include superconducting electronics, cryogenic semiconductor electronics, and quantum computing.

Superconducting electronic systems typically consist of medium-scale integrated circuits based on niobium Josephson junctions, which operate at cryogenic temperatures of around 4 K. Applications are developing in digital signal processing at radio frequencies, and ultra-low-power computers.

Cryogenic semiconductor electronics may be designed to operate below 100 K, or even less than 1 K. These are typically interface circuits for cryogenic sensor arrays and superconducting electronic systems.

Quantum computing systems are in the research stage, with many alternative technologies being explored for making arrays of quantum bits or “qubits”. The leading technologies at present are superconducting circuits and trapped ions, but others are surveyed as well.

Access the CEQIP chapter at the IRDS™ website.

This is available online without charge, however, users must first subscribe to the IRDS™ Technical Community.

Other IRDS™ Chapters are available at the IRDS™ website.

A video overview by Dr. Holmes about the CEQIP chapter last year is also available at IEEE.tv.

The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design

At the International Solid State Circuits Conference (ISSCC) in San Francisco, California, USA in February 2020, Dr. Jeff Dean of Google presented an overview of how Google sees the present and future of machine learning (ML).

He presented several examples of recent dramatic improvements in deep learning based on many layers of neural networks, including voice recognition, computer vision, language translation, and more generic “reinforcement learning”.

He distinguished initial training the neural network, which may be quite time-consuming, from subsequent fast operation of the optimized network, known as inference.

He pointed out that tremendous improvements in performance have been achieved with specialized hardware, which is quite different from traditional processors. For example, much of the computation is low-precision matrix multiplication in parallel. He featured the Google Tensor Processing Unit (TPU) chip for inference, which can operate in both data centers and in cell phones.

Finally, he described how Google is using Deep Learning in automated design and layout of the some of the same chips performing Deep Learning. Results indicate that such an automated system can be trained to perform as well as a human designer, but is orders of magnitude faster.

Access the video of Dr. Dean’s presentation.

Access a companion article in the ISSCC 2020 Proceedings at IEEE Xplore.

A preprint of this article is also available at arXiv.org.

Several other plenary talks from ISSCC 2020 are available at the ISSCC website.

• Rebooting Computing Video Overview
• IEEE Future Directions
• IEEE Future Directions Blog
• Computing in Science and Engineering on the End of Moore's Law
• IEEE Journal of Exploratory Solid-State Computational Devices and Circuits (JXCDC)
• Arch2030 Workshop Report
• Workshop on Neuromorphic Computing
• Workshop on Beyond CMOS Technology
• Update on National Strategic Computing Initiative (NSCI)
• RC White Paper on Nanocomputers
• IEEE Computer Magazine on Rebooting Computing
• RC-ITRS Report on the Foundation of the New Computer Industry Beyond 2020