Tackling traditional and AI computing challenges with FPGA accelerators

使用 FPGA 加速器应对传统和人工智能计算挑战

• 批准号: ST/W00576X/1
• 负责人: Alessandro Cerri
• 金额: $ 7.52万
• 依托单位: University of Sussex
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FW00576X%2F1
• 关键词: Tackling; traditional; AI; computing; challenges

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 similartechniques are relevant in disparate fields such as medical imaging, the processing of digital images and the identification of genetic sequences and markers inlaboratory samples.

用这些资金购买的设备可以探索新颖的解决方案，以满足实验粒子物理及其他领域的快速计算需求。它的直接应用将是解决高能物理实验中穿过探测器的粒子签名的识别问题，但类似的技术是相关的在医学成像、数字图像处理以及实验室样本中基因序列和标记物的识别等不同领域。