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HKU chip performs search task 100 million times faster than standard CPU_我的网站

一 | 本报讯 近日,县税务局特别邀请县消防救援大队联合开展消防安全知识培训和应急疏散救援演练活动。 (ECNS) -- Researchers at The University of Hong Kong (HKU) have developed a minimalist analogue content-addressable memory (CAM) chip that performs complex searches directly where data are stored, the university said Tuesday. When tasked with calculating the analogue Hamming distance for machine learning classification, the new analogue CAM performed the task approximately 108 (100 million) times faster than a standard CPU, scoring exceptionally high accuracy across multiple datasets, according to the university. The chip is designed to reduce the slow and energy-intensive transfer of data between memory and processors, known as the “von Neumann bottleneck.” Its architecture can compare incoming search data with all stored data simultaneously in a single step. Led by professor Li Can from the Department of Electrical and Computer Engineering of the Faculty of Engineering and the Centre for Advanced Semiconductors and Integrated Circuits (CASIC), the team built each analogue CAM cell with just two transistors, compared with up to 16 in a conventional digital CAM cell. The design reduces chip area and allows continuous analogue signals to be processed directly. Li said the team is exploring how the technology could support search mechanisms in large AI models. The findings were published in Nature Nanotechnology. (By Intern Yang Hongran, Zhang Dongfang)
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在培训讲座环节,邀请了建昌县消防救援大队防火监督员王维担任主讲。王维通过真实的火灾案例,用通俗易懂的语言讲述了消防安全的重要性,就防火、灭火、逃生、自救四个方面进行了重点阐述,并介绍了消防意识的重要性、火场中易出现的延误逃生时机的误区、自救逃生的方法等一系列消防安全知识。
在演练环节中,忽然听到紧急的警报声,各楼层安全员迅速按紧急预案的疏散线路引导楼内人员,打湿毛巾,捂住口鼻,压低身体,有序撤离。很快大家集中到室外安全地带,楼层安全员迅速清点人数,并向总指挥报告。整个演练过程有条不紊,达到了预期效果。

二 | 县消防救援大队朝阳路消防救援站副站长李刘钹对整个演练进行了点评。 活动中,税务干部实地观摩车辆器材性能和实战效能,消防战士们昂扬的战斗意志和精湛的业务水平引发现场同志们的阵阵喝彩。消防员现场就灭火器和消防水带的使用方法和技能向大家进行讲解和操练,安全员和青年干部上阵体验“灭火”,进一步提升消防器材的使用技能。(王桂琳 刘文婷)。
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