CoolAir Temperature- and Variation- Aware Management for Free- Cooled Datacenters Íñigo Goiri, Thu D. Nguyen, and Ricardo Bianchini 1
CoolAir Temperature- and Variation-Aware Management for Free-Cooled Datacenters Íñigo Goiri, Thu D. Nguyen, and Ricardo Bianchini 1.
Dec 23, 2015
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Transcript
- Slide 1
- CoolAir Temperature- and Variation-Aware Management for Free-Cooled Datacenters igo Goiri, Thu D. Nguyen, and Ricardo Bianchini 1
- Slide 2
- Hybrid: typical + free cooling Typical datacenter cooling Filters Evaporative cooler Fans Server racks Outside air Cooling tower Water chiller Air handling unit Server racks Microsoft DC in Chicago 2 Free cooling
- Slide 3
- Potentially negative impact on hardware reliability, especially disks High temperature Wide temperature variation High humidity Free cooling limitations 3 Outside Disk Inlet Outside temp directly impacts inlet and disk temps Daily temperature variation can be large
- Slide 4
- Roadmap Motivation and background CoolAir: Managing free-cooled datacenters Cooling modeling Cooling management Compute management CoolAir for Parasol Evaluation and general lessons Conclusions 4
- Slide 5
- Energy-aware management of cooling & workload Minimize hardware reliability issues Limit temperature and relative humidity Reduce temperature variation Major tasks 1.Predict conditions and energy 2.Select best cooling settings 3.Apply cooling settings 4.Place and schedule load CoolAir Datacenter CoolAir: Managing free-cooled datacenters Cooling Servers Cooling Manager Compute Manager Cooling Modeler Weather Forecast 5
- Slide 6
- Predictions based on linear regression model Datacenter Cooling modeling Historic Data Cooling Learner Cooling Model Temperature inside Humidity inside Cooling power Temperature outside Location in the datacenter Datacenter utilization Cooling setting Temperature inside/outside Humidity outside Cooling setting Cooling operation 6
- Slide 7
- Use predictions from cooling model Reduce variation with a temp band based on expected outside temp Maintain temperature within the band Middle: forecast outside temp + offset Periodically Predict environmentals and energy Select best settings using utility Apply cooling settings Cooling management Band selection example Temperature 7 Average Outside temperature forecast Hour 06 12 2418 Offset
- Slide 8
- Compute management Spatial placement Distribute load to servers Group servers into pods of similar behavior Reduce solving and modeling complexity Favor pods with higher heat recirculation Against common practice in non-free-cooled DCs Lower recirculation pods are closer to cooling temperature variation Temporal scheduling When to execute deferrable loads (see paper) 8 Sensors Server Pod Front view of Parasols racks Rack 1 Rack 2
- Slide 9
- Roadmap Motivation and background CoolAir: Managing free-cooled datacenters CoolAir for Parasol Evaluation and general lessons Conclusions 9
- Slide 10
- Case study: Parasol Default cooling controller: Outside temperature 30C Free cooling with variable fan speed Outside temperature > 30C AC cycling with hysteresis External view Internal layout (top view) Exhaust Free Cooling Rack 1 Rack 2 Cold aisleHot aisle Cooling Controller Door Relays Partition Air duct 10 Air Conditioner
- Slide 11
- CoolAir for Parasol Data collection and model learning Historical sensor info for two months Generated extreme settings to learn faster Cooling configurer Interface with Parasols thermostat Control fan speed and AC Compute configurer for Hadoop Send idle worker nodes to sleep while keeping data available >90% with
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