Quantum Leaps

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–Jeff Child, Editor-in-Chief

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Throughout my career, I’ve always been impressed by Intel’s involvement in a wide spectrum of computing and electronics technologies. These range from the mundane and practical on one hand, to forward-looking and disruptive advances on the other. A lot of these weren’t technologies for which Intel ever intended to take direct advantage of over the long term. I think a lot about how Intel facilitated the creation of and early advances in USB. Intel even sold USB chips in the first couple years of USB’s emergence, but stepped aside from that with the knowledge that their main focus was selling processors.

USB made computers and a myriad of consumer electronic devices better and easier to use, and that, Intel knew, advanced the whole industry in which their microprocessors thrived. Today, look around your home, your office and even your car and count the number of USB connectors there are. It’s pretty obvious that USB’s impact has been truly universal.

Aside from mainstream, practical solutions like USB, Intel also continues to participate in the most forward-looking compute technologies. Exemplifying that, in January at the Consumer Electronics Show (CES) show in Las Vegas, Intel announced two major milestones in its efforts to develop future computing technologies. In his keynote address, Intel CEO Brian Krzanich announced the successful design, fabrication and delivery of a 49-qubit superconducting quantum test chip. The keynote also focused on the promise of neuromorphic computing.

In his speech, Krzanich explained that, just two months after delivery of a 17-qubit superconducting test chip, Intel that day unveiled “Tangle Lake,” a 49-qubit superconducting quantum test chip. The chip is named after a chain of lakes in Alaska, a nod to the extreme cold temperatures and the entangled state that quantum bits (or “qubits”) require to function.

According to Intel, achieving a 49-qubit test chip is an important milestone because it will allow researchers to assess and improve error correction techniques and simulate computational problems.

Krzanich predicts that quantum computing will solve problems that today might take our best supercomputers months or years to resolve, such as drug development, financial modeling and climate forecasting. While quantum computing has the potential to solve problems conventional computers can’t handle, the field is still nascent.

Mike Mayberry, VP and managing director of Intel Labs weighed in on the progress of the efforts. “We expect it will be 5 to 7 years before the industry gets to tackling engineering-scale problems, and it will likely require 1 million or more qubits to achieve commercial relevance,” said Mayberry.

Krzanich said the need to scale to greater numbers of working qubits is why Intel, in addition to investing in superconducting qubits, is also researching another type called spin qubits in silicon. Spin qubits could have a scaling advantage because they are much smaller than superconducting qubits. Spin qubits resemble a single electron transistor, which is similar in many ways to conventional transistors and potentially able to be manufactured with comparable processes. In fact, Intel has already invented a spin qubit fabrication flow on its 300-mm process technology.

At CES, Krzanich also showcased Intel’s research into neuromorphic computing—a new computing paradigm inspired by how the brain works that could unlock exponential gains in performance and power efficiency for the future of artificial intelligence. Intel Labs has developed a neuromorphic research chip, code-named “Loihi,” which includes circuits that mimic the brain’s basic operation.

While the concepts seem futuristic and abstract, Intel is thinking of the technology in terms of real-world uses. Intel says Neuromorphic chips could ultimately be used anywhere real-world data needs to be processed in evolving real-time environments. For example, these chips could enable smarter security cameras and smart-city infrastructure designed for real-time communication with autonomous vehicles. In the first half of this year, Intel plans to share the Loihi test chip with leading university and research institutions while applying it to more complex data sets and problems.

For me to compare quantum and neuromorphic computing to USB is as about as apples and oranges as you can get. But, who knows? When the day comes when quantum or neuromorphic chips are in our everyday devices, maybe my comparison won’t seem far-fetched at all.

This appears in the February (331) issue of Circuit Cellar magazine

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The Quest for Extreme Low Power

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–Jeff Child, Editor-in-Chief

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Over the next couple years, power will clearly rank as a major design challenge for the myriad of edge devices deployed in Internet of Things (IoT) implementations. Such IoT devices are wireless units that need to be always on and connected. At the same time, they need low power consumption, while still being capable of doing the processing power needed to enable machine intelligence. The need for extreme low power in these devices goes beyond the need for long battery life. Instead the hope is for perpetually powered solutions providing uninterrupted operation—and, if possible, without any need for battery power. For their part, microcontroller vendors have been doing a lot in recent years within their own labs to craft extreme low power versions of their MCUs. But the appetite for low power at the IoT edge is practically endless.

Offering a fresh take on the topic, I recently spoke with Paul Washkewicz, vice president and co-founder of Eta Compute about the startup’s extreme low power technology for microcontrollers. The company claims to offer the lowest power MCU intellectual property (IP) available today, with voltages as low as 0.3 V. Eta Compute has developed and implemented a unique low power design methodology that delivers up to a 10x improvement in power efficiency. Its IP and custom designs operate over severe variations in conditions such as temperature, process, voltage and power supply variation. Eta Compute’s approach is a self-timed technology supporting dynamic voltage scaling (DVS) that is insensitive to process variations, inaccurate device models and path delay variations.

The technology has been implemented in a variety of chip functions. Among these are M0+ and M3 ARM cores scaling 0.3 V to 1.2 V operation with additional low voltage logic support functions such as real-time clocking (RTC), Advanced Encryption Standard (AES) and digital signal processing. The technology has also been implemented in an A-D converter sensor interface that consumes less than 5 µW. The company has also crafted an efficient power management device that supports dynamic voltage scaling down to 0.25 V with greater than 80% efficiency.

According to the company, Eta Compute’s technology can be implemented in any standard foundry process with no modifications to the process. This allows ease of adoption of any IP and is immune to delays and changes in process operations. Manufacturing is straightforward with the company’s IP able to port to technology nodes at any foundry. Last fall at ARM TechCon, David Baker, Ph.D. and Fellow at Eta Compute, did a presentation that included a demonstration of a small wireless sensor board that can operate perpetually on a small 1 square inch solar cell.

Attacking the problem from a different direction, another startup, Nikola Labs, is applying its special expertise in antenna design and advanced circuitry to build power harvesting into products ranging from wearables to sensors to battery-extending phone cases. Wi-Fi routers, mobile phones and other connected devices are continually emitting RF waves for communication. According to the company, radio wave power is strongest near the source—but devices transmit in all directions, saturating the surrounding area with stray waves. Nikola Labs’ high-performance, compact antennae capture this stray RF energy. Efficient electronics are then used to convert it into DC electricity that can be used to charge batteries or energize ultra-low power devices.

Nikola’s technology can derive usable energy from a wide band of frequencies, ranging from LTE (910 MHz) to Wi-Fi (2.4 GHz) and beyond (up to 6 GHz). Microwatts of power can be harvested in an active ambient RF area and this can rise to milliwatts for harvesters placed directly on transmitting sources. Nikola Labs has demonstrated energy harvesting from a common source of RF communication waves: an iPhone. Nikola engineers designed a case for iPhone 6 that captures waste RF transmissions, producing up to 30 mW of power to extend battery life by as much as 16% without impacting the phone’s ability to send and receive data.

Whether you address the challenge of extreme low power from the inside out or the outside in—or by advancing battery capabilities—there’s no doubt that the demand for such technologies will only grow within the coming years. With all that in mind, I look forward to covering developments on this topic in Circuit Cellar throughout 2018.

This appears in the January (330) issue of Circuit Cellar magazine

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December Circuit Cellar: A Sneak Preview

The December issue of Circuit Cellar magazine is coming soon. Want a sneak peak? We’ve got a great selection of excellent embedded electronics articles for you.

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 Here’s a sneak preview of December Circuit Cellar:

MICROCONTROLLERS IN MOTION

Special Feature: Electronics for Wearable Devices
Circuit Cellar Chief Editor Jeff Child examines how today’s microcontrollers, sensors and power electronics enable today’s wearable products.

329 Cover Screen CapSimulating a Hammond Tonewheel Organ
(Part 2)

Brian Millier continues this two-part series about simulating the Hammond tonewheel organ using a microcontrollers and DACs. This time he examines a Leslie speaker emulation.

Money Sorting Machines (Part 1)
In this new article series, Jeff Bachiochi looks the science, mechanics and electronics that are key to sorting everything from coins to paper money. This month he discusses a project that uses microcontroller technology to sort coins.

Designing a Home Cleaning Robot (Part 1)
This four-part article series about building a home cleaning robot starts with Nishant Mittal discussing his motivations behind to his design concept, some market analysis and the materials needed.

SPECIAL SECTION: GRAPHICS AND VISION

Designing High Performance GUI
It’s critical to understand the types of performance problems a typical end-user might encounter and the performance metrics relevant to user interface (UI) design. Phil Brumby of Mentor’s Embedded Systems Division examines these and other important UI design challenges.

Building a Robotic Candy Sorter
Learn how a pair of Cornell graduates designed and constructed a robotic candy sort. It includes a three degree of freedom robot arm and a vision system using a Microchip PIC32 and Raspberry Pi module.

Raster Laser Projector Uses FPGA
Two Cornell graduates describe a raster laser projector they designed that’s able to project images in 320 x 240 in monochrome red. The laser’s brightness and mirrors positions are controlled by an FPGA and analog circuitry.

ELECTRICITY UNDER CONTROL

Technology Spotlight: Power-over-Ethernet Solutions
Power-over-Ethernet (PoE) enables the delivery of electric power alongside data on twisted pair Ethernet cabling. Chief Editor Jeff Child explores the latest chips, modules and other gear for building PoE systems.

Component Overstress
When an electronic component starts to work improperly, Two likely culprits are electrical overstress (EOS) and electrostatic discharge (ESD). In his article, George Novacek breaks down the important differences between the two and how to avoid their effects.

AND MORE FROM OUR EXPERT COLUMNISTS:

Writing the Proposal
In this conclusion to his “Building an Embedded Systems Consulting Company” article series, Bob Japenga takes a detailed look at how to craft a Statement of Work (SOW) that will lead to success and provide clarity for all stakeholders.

Information Theory in a Nutshell
Claude Shannon is credited as one of the pioneers of computer science thanks to his work on Information Theory, informing how data flows in electronic systems. In this article, Robert Lacoste provides a useful exploration of Information Theory in an easily digestible way.