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To address challenges associated with extremely large data volumes and rates, SLAC’s Computer science division works with Stanford and Silicon Valley partners on innovative computational solutions.

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SRCF-II construction

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SLAC is leading an effort to build a network that will enable AI and machine learning to steer experiments and more.

Images of molecules, spirals, and lasers surround a lens peering on the earth.
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Digital design engineer Abhilasha Dave’s passion for connecting machine learning and hardware is helping SLAC solve big data challenges.

Photo of Abhilasha Dave in her office
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David Cesar, Julia Gonski and W.L. Kimmy Wu will each receive $2.75 million issued over five years for their research in X-ray and ultrafast...

Early Career Award Winners 2024
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Scientists have developed an AI-based method that helps gather data more efficiently in the search for new materials, allowing researchers...
self driving experiments
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The method could lead to the development of new materials with tailored properties, with potential applications in fields such as climate change, quantum computing...

self driving experiments
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SLAC works with two small businesses to make its ACE3P software easier to use in supercomputer simulations for optimizing the shapes of accelerator structures.

A large, complex shape is seen against a blue background crisscrossed with white lines. The shape is dark blue and resembles a brick partially topped with a thick shark’s fin. Three areas of bright red, orange and green, are on the shape’s bottom edge.
Illustration

With help from two small businesses, SLAC’s vintage ACE3P software is spreading its wings to make supercomputing easier and faster.

A large, complex shape is seen against a blue background crisscrossed with white lines. The shape is dark blue and resembles a brick partially topped with a thick shark’s fin. Three areas of bright red, orange and green, are on the shape’s bottom edge.
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An extension of the Stanford Research Computing Facility will host several data centers to handle the unprecedented data streams that will be produced by...

SRCF-II
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The leaders of SLAC's Technology Innovation Directorate discuss how their group supports the lab's most innovative projects.

TID senior managers
Press Release

They discover a short-lived state that could lead to faster and more energy-efficient computing devices.

ultrafast switching
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Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.

Physicist Daniel Ratner.
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Two projects will look for ways to link individual quantum devices into networks for quantum computing and ultrasensitive detectors.

QIS microantenna