Tackling traditional and AI computing challenges with FPGA accelerators
Lead Research Organisation:
University of Sussex
Department Name: Sch of Mathematical & Physical Sciences
Abstract
The equipment purchased with these funds allows the exploration of novel solutions to the need for fast computing in experimental particle physics and beyond.
Its immediate application will be to the problem of identifying signatures of particles traversing detectors in high energy physics experiments, however similar
techniques are relevant in disparate fields such as medical imaging, the processing of digital images and the identification of genetic sequences and markers in
laboratory samples.
Its immediate application will be to the problem of identifying signatures of particles traversing detectors in high energy physics experiments, however similar
techniques are relevant in disparate fields such as medical imaging, the processing of digital images and the identification of genetic sequences and markers in
laboratory samples.
