One of the things that makes the main particle accelerator at the U.S. Department of Energy's Thomas Jefferson National Accelerator Facility unique is that it was the first linear accelerator to ...

A cohort of 20 undergraduate and first-year graduate students in computer science, computer engineering, and electrical engineering from Northwestern University, University of Illinois Chicago (UIC), ...

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control. By integrating virtual ...

A computer-generated image based on a generative diffusion process shows 2D projections of a particle accelerator beam. Starting from pure noise, signals from the accelerator adaptively guide the ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...

A technical paper titled “SpikeHard: Efficiency-Driven Neuromorphic Hardware for Heterogeneous Systems-on-Chip” was published by researchers at Columbia University. “Neuromorphic computing is an ...

A major design challenge facing numerous silicon design teams in 2023 is building the right amount of machine learning (ML) performance capability into today’s silicon tape out in anticipation of what ...

Adobe, Baidu, Netflix, Yandex. Some of the biggest names in social media and cloud computing use NVIDIA CUDA-based GPU accelerators to provide seemingly magical search, intelligent image analysis and ...

Moving machine learning to the edge has critical requirements on power and performance. Using off-the-shelf solutions is not practical. CPUs are too slow, GPUs/TPUs are expensive and consume too much ...