Lightmatter touts optical processor chip for artificial intelligence applications

Aug. 18, 2020
The device uses light instead of electronics to compute and transport data within the chip. The photonic approach reduces heat dissipation and improves processor speed, says the company.

Boston-based startup Lightmatter says it is debuting a photonics-based processor chip designed to perform artificial intelligence (AI) inference acceleration at this week’s Hot Chips virtual event. Lightmatter Vice President of Engineering Carl Ramey is scheduled to present the photonic processor architecture today as part of the program.

The device uses light instead of electronics to compute and transport data within the chip. The photonic approach reduces heat dissipation and improves processor speed, says the company. Such performance and thermal improvements will be necessary as AI demands increase, Lightmatter points out.

“The Department of Energy estimates that by 2030, computing and communications technology will consume more than 8% of the world’s power. Transistors, the workhorse of traditional processors, aren’t improving; they’re simply too hot. Building larger and larger data centers is a dead-end path along the road of computational progress,” said Nicholas Harris, PhD, founder and CEO at Lightmatter. “We need a new computing paradigm. Lightmatter’s optical processors are dramatically faster and more energy efficient than traditional processors. We’re simultaneously enabling the growth of computing and reducing its impact on our planet.”

Lightmatter says the 3D-stacked chip package contains more than 1 billion FinFET transistors, tens of thousands of photonic arithmetic units, and hundreds of “record-setting” data converters. The photonic processor runs standard machine learning frameworks including PyTorch and TensorFlow to enable advanced AI algorithms, the company adds.

Lightmatter was founded by Harris, Darius Bunandar (chief scientist), and Thomas Graham (COO). The company is backed by GV (formerly Google Ventures), Matrix Partners, and Spark Capital. It raised $33 million in Series A funding, including a $22 million Series A-1 funding round announced in February 2019.

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