UCLA Gets Domain-Specific Healthcare Computing Grant

A group led by UCLA engineering researchers that designs high-performance, customizable computer technologies to improve healthcare has received a $3 million grant from a public-private partnership between the National Science Foundation and semiconductor manufacturer Intel Corp.


A group led by UCLA engineering researchers that designs high-performance, customizable computer technologies to improve healthcare has received a $3 million grant from a public-private partnership between the National Science Foundation and semiconductor manufacturer Intel Corp.

The award will help further the long-term efforts of the university's Center for Domain-Specific Computing group, which aims to speed up the computing side of medicine through innovations in what is known as domain-specific computing. Their research has the potential to reduce radiation exposure during CT scans and lead to the development of patient-specific cancer treatments.

In developing their healthcare computing innovations, CDSC researchers have focused on domain-specific computing, which has significant advantages over general-purpose computing in medical applications. In domain-specific computing, researchers create custom hardware that can solve a range of related problems within a particular area or domain with high efficiency and flexibility--as opposed to the specialized circuits used to solve only a single problem in cell phones, personal computers and other devices.

This customization allows the team to achieve power and efficiency orders of magnitude higher than what can be reached with general-purpose computing, said Jason Cong, director of the CDSC and the UCLA Chancellor's Professor of Computer Science.

With the new funding, the team will focus on developing accelerator-rich architectures that can be applied to medical imaging and patient-specific cancer treatments. Using their customizable, heterogeneous platform, Cong and his team have been able to make one of the leading CT image-reconstruction algorithms nearly a hundred times faster, which could significantly reducing a patient's exposure to radiation. In May, the researchers presented their results at the IEEE International Symposium on Field-Programmable Custom Computing Machines.

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