Observatories and telescopes, lasers and X-ray light sources, and other high-throughput instruments generate image data faster than CPU-bound pipelines can process it to support timely decisions. The computational bottleneck is rarely one slow kernel. It’s the whole path from data in the sensor to a decision: read the raw data, match point-spread functions or detector responses, subtract or reduce, fit, classify, and alert.

Modern facilities routinely accumulate petabytes of multidimensional data across a single survey or experiment campaign. With CPU-first implementations, it can take hours to months—sometimes a year or more—to obtain scientifically useful results from data the instrument produced in seconds. These delays make it harder for scientists and engineers to extract insights and advance their research.…