IEEE Awards Booklet - 2020 - 6

2020 IEEE SPECTRUM'S CORPORATE AWARDS

IEEE Spectrum Technology in the Service of
Society Award

IEEE Spectrum Emerging Technology Award
Sponsored by IEEE Spectrum

Sponsored by IEEE Spectrum

A traditional hospital ultrasound system sits on a wheeled cart,
weighs 40 kilograms, can cost as much as $200,000, and requires
a trained specialist to operate. Today, after decades-long development efforts, ultrasound transducers are available that connect to a
smartphone or tablet, cost a few thousand dollars, and can be easily carried in a lab-coat pocket. The transducers are ergonomic,
lightweight, use very little power (~2watts), don't overheat and
were designed for rugged environments.
Philips Ultrasound, in Bothell, Washington, introduced one
of the first app-based ultrasound systems, called Lumify, in 2015.
Since then, portable devices such as Lumify have transformed
healthcare in remote and rural villages, especially, where they have
delivered powerful diagnostics capabilities and saved countless
lives. In some communities in Africa, South America, and Asia,
the nearest X-ray, CT, or MRI scanner is many hundreds of kilometers away. And yet an app-based, portable system can acquire
images and instantly upload them to the cloud for further evaluation, by a human specialist anywhere in the world or, in some
cases, a machine-learning program.
The Lumify system also has an included tele-ultrasound capability to let clinicians collaborate remotely in real time. While
performing a scan on a patient, and while using the built-in Reacts tele-ultrasound capability, either device camera, voice and live
ultrasound image can be streamed to a collaborator anywhere else
in the world. The smartphone's front-facing camera can be used
to show the position of the transducer alongside the resulting
ultrasound. These features enable even relatively inexperienced
users to provide better healthcare. In the developing world and
other austere environments, these app-based systems have made
particularly important strides not just in obstetrics but also in detecting diseases such as pneumonia and in scanning organs for
evidence of goiter, cancer, and other diseases and injuries.

In the 70-year history of the computer industry, the largest chip
ever built contained 21 billion transistors and was about 814
square millimeters. In August 2019, Cerebras delivered a chip,
named the Wafer Scale Engine (WSE), that contains 1.2 trillion
transistors and is 46,225 millimeters square. The WSE is the first
and only trillion transistor processor. It is 56 times larger than
the next largest chip. It has 78 times more compute cores, with a
whopping 400,000 compute cores compared to the next largest,
at 5,280 cores. The WSE contains 3,000 times more fast on-chip
memory than the nearest competitor and has 33,000 times the
fabric bandwidth.
For artificial intelligence (AI) work, large chips process information more quickly, producing answers in less time. The WSE is
built and optimized for AI work. AI work-specifically training
neural networks--that before took months to compute, now takes
minutes with the WSE. And problems that took weeks can now
be done in seconds. This order of magnitude acceleration allows
AI researchers to ask more questions and find more answers per
unit time.
To learn more, read IEEE Spectrum's article: Cerebras's Giant
Chip Will Smash Deep Learning's Speed Barrier.

6 | 2020 IEEE AWARDS BOOKLET


https://spectrum.ieee.org/semiconductors/processors/cerebrass-giant-chip-will-smash-deep-learnings-speed-barrier

IEEE Awards Booklet - 2020

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IEEE Awards Booklet - 2020 - Cover1
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IEEE Awards Booklet - 2020 - 1
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IEEE Awards Booklet - 2020 - Table of Contents
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