Shawn | China HVAC @sundmop
Decoding China's HVAC & building energy for the world. Heat pumps, data center cooling, ESCO, smart buildings. Insider view. ÜT: 30.287863,120.146864 Joined February 2009-
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9 p.m. in China. The classrooms are still lit. Students are still at evening self-study — wanzixi — grinding through homework long after dinner. For millions of Chinese high schoolers, the school day doesn’t end when the sun goes down. It ends when the lights finally go out.
Midea's response: extend its HVAC lifecycle data chain into AI data centers. A data center shouldn't chase one efficiency metric. Lowest energy use ≠ best system, especially when a low-energy strategy doesn't fit current business risk. "Optimal" must balance efficiency, reliability, equipment health, redundancy and cost.
AI is changing how data center HVAC is designed. Midea - the leading Chinese HVAC maker - gave its opinion: the question is no longer "how do we deliver cooling?" It's how to dynamically match compute load with cooling, under hard reliability constraints. Four things have changed 🧵 #AIDC #coolingsystem
4. The pace AI compute iterates quarterly. Design-to-power-on windows keep shrinking, and rack additions, power upgrades and liquid-cooling retrofits keep coming. If design, delivery and operation work in silos, every expansion means re-simulating, re-commissioning, re-calibrating.
3. The constraints In data centers, thermal safety and business continuity are hard limits. An unplanned outage costs entire batches of compute, not just electricity. Systems must keep trading redundancy (availability) against efficiency (cost). The two pull in opposite directions.
2. The chain Cooling now extends to the IT side: Chiller → primary loop → CDU → secondary loop → cold plate → chip Air, cold-plate and immersion cooling can coexist. Each segment has its own temperature, flow, pressure and response time. The most efficient single unit ≠ the optimal chain.
1. The load Building cooling loads are fairly smooth. AI loads aren't. Rack density has jumped from 6–8 kW to 30, 50, even 100+ kW, and swings sharply with job scheduling. Size for static peak, and you run inefficiently most of the time, or approach thermal limits when load spikes.
#ai #cooling Why does AI use so much electricity? A big part of the answer is not computing. It's cooling. Chips turn almost all the power they use into heat. That heat has to go somewhere, or the servers shut down. In many data centers, cooling is one of the largest energy costs after the servers themselves.
which one will u choose ?
觅得一壶，可煮人间清欢。
《衡量锻炼强度的标准：代谢当量》图片版
中国官方媒体10月27日突然宣布，今年刚刚卸任的中共政治局常委兼国务院总理李克强去世，享年68岁。官媒宣称李克强“近日在上海休息”，“10月26日因突发心脏病，经全力抢救无效，于10月27日0时10分在上海逝世。”正式讣告后将随后发表。 李克强在2012年的中共十八大成为排名第二、仅次于习近平的中共政治局常委，并在第二年当选为国务院总理。当时国际社会曾有“习李新政”之说，但实际上习近平过去十年独掌大权，李克强连一个副部级官员的提名权都没有，习近平并在2018年修改宪法，废除了国家主席任期限制，而李克强则在任职两届之后卸任所有党政领导职务。 李克强之死肯定会在党内引起巨大争议，究竟是因为心脏病突发还是残酷的政治斗争，后续会有许多消息传出。
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风骚啊RT @wangpei: 在太平洋电脑城苹果配件店用新买的蓝牙键盘测试发推,我今天下午必须用ipad写一篇约稿.
RT @VOAChinese: 中国称赞苏丹选举“平稳有序”: 中国称赞苏丹24年来首次多党派选举“取得成功”。一天前，美国批评苏丹选举既不自由也不公平。中国外交部发言人姜瑜说，中国监督苏丹总统和议会选举的代表团认为选举“平稳有序”。 http://bit.ly/9l1nsM
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