Spectrometers measure the light spectrum to gauge the amount and type of chemicals present in a given sample of material. But even today’s powerful smartphone cameras were never intended for this kind of intensive optical analysis.

“The camera was never designed for sampling,” says Li. “It was designed for taking pictures at a distance.” To compensate for the limitations of tiny lenses, Li and his team fashioned a special prism array capable of dividing incoming light into waves for processing. Most of the technical challenges came in trying to fabricate the prism array itself; the software application was comparatively easy to develop using standard image processing routines.

In the past, large hospitals would have expected to pay up to $500,000 for a top-of-the-line spectrometer; a more basic model might run as little as $10,000. While Li’s device won’t fully supplant those kinds of machines, it could make spectrometer-based analysis available to smaller hospitals and clinics in rural areas or developing countries, thus bringing the technique within reach of patients who might otherwise never have access to this kind of diagnostic capability.

At the University of Washington, a team of doctors and engineers partnered to create a smartphone-based device called BiliCam that allows doctors and new parents to identify signs of jaundice, a common affliction of newborn babies.

The system consists of an app that invokes a standard smartphone camera and flash, along with a printed card used to calibrate color with a range of different lighting conditions and skin tones. By taking a photo of the baby’s skin in proximity to the card, a parent or healthcare provider can then use the app to submit the photo to a cloud-based system that analyzes the data using machine-learning algorithms, then generates a report on the baby’s bilirubin levels that it can send back almost instantly to a parent’s smartphone.

Beyond image-processing applications, the sheer computing power of smartphones—the Samsung S7 handset now boasts far more processing power than a supercomputer from the mid-1990s—opens the door to a wide range of other pocket-sized scientific instruments.

In the U.K., a company called Oxford Nanopore Technologies builds compact devices known as nanopore sequencers for genetic analysis; they utilize a highly cost-effective approach that allows a single molecule of DNA or RNA to be analyzed via electrical conductivity (as opposed to more resource-intensive solid-state methods). The method makes genetic sequencing more readily available to researchers for a wide range of purposes: identifying pathogens in food or water, monitoring environmental conditions for climate science, or even sequencing the human genome. Nanopore sequencing also holds promise for a wide range of other scientific applications including plant research, population genomics, and microbiology.

In 2014, the company released MinION, a nanopore sequencer that weighs under 100 grams and plugs into a PC or laptop via a USB cable. With prices starting at $1,000, the device is making genetic sequencing widely available to a range of researchers who might not otherwise have access to sequencing technology. It has already been used for surveillance of Zika in Brazil and Ebola in Guinea, and has even found its way onto the International Space Station.

Oxford Nanopore is now taking this work a step further with its as-yet-unre-leased SmidgION, a sequencer attachment that snaps onto a smartphone running specialized software.

The proliferation of mobile processing power will not only make high-powered scientific instruments more readily available to researchers,

At the University
of Washington, a
smartphone-based
device allows doctors
and new parents
to identify signs
of jaundice,
an affliction common
to newborn babies.

Milestones

Labarta Recognized with ACM-IEEE Kennedy Award

ACM and IEEE recently named Jesús Labarta of the Barcelona Supercomputing Center and Universitat Politècnica de Catalunya as the recipient of the 2017 ACM-IEEE CS Ken Kennedy Award.

Labarta was recognized for his seminal contributions to programming models and performance analysis tools for high performance computing.

Throughout his career, Labarta has developed tools for scientists and engineers working in parallel programming. In the programming models area, he made fundamental contributions to the concept of asynchronous task-based models and intelligent runtime systems. In the performance tools area, Labarta’s team develops and distributes Open Source Barcelona Supercomputer Center tools designed to analyze an application’s behavior and identify issues that may impact performance.

Labarta is director of the Computer Science Department at the Barcelona Supercomputing Center and a professor of Computer Architecture at the Universitat Politècnica de Catalunya.

From 1996 to 2004 he served as director of the European Center of Parallelism of Barcelona. He has been involved in research and cooperation with many leading companies on HPC-related topics. Currently, he is the leader of the Performance Optimization and Productivity EU Center of Excellence, where more than 100 users (both academic and SMEs) from a very wide range of application sectors receive performance assessments and suggestions for code refactoring efforts.

ACM and IEEE co-sponsor the Kennedy Award, which was established in 2009 to recognize substantial contributions to programmability and productivity in computing and significant community service or mentoring contributions. The Award carries a $5,000 honorarium endowed by the SC Conference Steering Committee.