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“热IT”是虚假经济?温度和位置对效率的真正影响.pdf

上传人: 张** 编号:158217 2024-03-31 14页 3.16MB

1、OCP Regional Summit|April 19,2023|Prague,CZRichard KennyManaging Director,InteractGroup Research and Sustainability Director,TechbuyerVisiting Research Fellow London South Bank University(LSBU)School of Engineering“Hot IT”a false economy?The true impact of temperature and location on efficiencyDCD a

2、rticle February 2023Movement towards higher temperature envelopesEvidence of energy savings as a resultDecreased incidence of failure as a result But is this the full story?Raising temperatures a false economy?Enterprise servers,not OCP hardwareServer age variation 2012-2017 release date Primary var

3、iable is CPUAir cooled,not liquid cooledAiredale case study of LDEX DC3Assuming homogeneous racks of profiled serversModelling for enterpriseEnvironmental control:Temperature:15-35CPressure:0-25Pa Laminar flow at server inletBenchmarking with SPEC SERTVariation limited to 20-30C,aligns with ASHRAE r

4、ecommendedPressure tested at 0Pa and 20Pa(Compatible with Open Rack width equipment)First benchmark testing,published IEEE Profiling Results:EfficiencyEfficiency scores drop due to power increases,workload performance unaffected.Other factors coming into playEffects of temperature and pressure most

5、obvious at extremes of utilisation.2-6%more power due to temperature.Reduced by 2-4%by increasing pressure.Oldest server(R620 E5-2690)worse performer at highest temperatures.R640 Silver 4116(A3 class)performs best.Least change due to temperature but low performance.Server Metrics(CPU)CPUs stay withi

6、n recommended ranges,small variation in power and temperaturesServer Metrics(Fan)Fan speeds increase significantly at higher temperatures,less so with higher pressures.Changes in fan speed dont wholly reflect changes in power.Cooling and utilizationTemp raised

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本文讨论了提高数据中心温度对效率的影响,并质疑了这种做法是否真的是经济的。研究发现,虽然提高温度可能会带来能源节约,但这也取决于多种因素。文章通过比较不同服务器在升高温度下的表现,发现旧服务器在高温下性能最差,而某些新服务器表现较好。同时,提高压力可以减少约2-4%的电力增加。在冷却和利用率方面,提高温度可能会增加IT负载和温差,从而抵消冷却方面的任何节能收益。研究还指出,不同气候条件下,冷却系统的能耗对温度升高的反应不同。最后,文章强调了解决这些问题需要实际世界的讨论,并将在会议中展示相关机器学习软件。
"高温下服务器效率如何变化?" "不同气候条件下冷却系统能耗对比如何?" "机器学习软件Interact在实际应用中的表现如何?"
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