1. Automated Cost-Aware Data Center Management (part 4)
Justin Moore
Advisor: Jeff Chase
Committee
Parthasarathy Ranganathan, Carla Ellis,
Alvin Lebeck, Jun Yang

2. Heat Recirculation Rebalance power, reduce cooling costsδQ
CRAC Q
Rebalance power, reduce cooling costs
Hot exhaust air mixes with cold incoming air
Cause: inefficient data center layout, air flow
[Sharma2003]

3. TARP: Results Less heat recirculation  lower cooling power cost
“Hot spots” can be OK and beneficial, provided heat is exiting
Workload inversely proportional to recirculation
Avoid until the last minute servers whose exhaust recirculates
Moore05Usenix

4. Cost-Aware Management
Identify primary sources of costs
Fixed: Acquisition
Dynamic: Power and Cooling
Cumulative: “Wear and tear”
Combine thermal costs with workload costs
Utility functions, SLAs, penalties, etc

5. - Reliability, utility, profitability
Ongoing Work: Models
Candidate
Settings
Policy
Workload
Weatherman
Cost Model
- Reliability, utility, profitability

6. Ongoing Work: Costs Per Day

7. Ongoing Work: Costs Per Day
Max inlet of 25C: even = 12.25C ($ / day) ; wman = 15.75C ($ / day)
Diff = $ / day ; $43, / year
0 wear-and-tear: even = 7.25C ($ / day) ; wman = 10.75C ($ / day)
Diff = $ / day ; $102, / year

8. Conclusions Need for comprehensive management Address new challenges
Power and thermal considerations are significant
Unified cost-aware management architecture
Extend MAPE architecture
Construct accurate models for instrumentation
Model and predict data-center-wide conditions
Formulate cost-aware management policies

9. Planning: Management Policies
Ad-hoc
Independent and limited in scope
Priority-based scheduling, thermal kill switches, …
Heuristic
Qualitative decisions based on “proxy” variables
i.e., Reduce power to reduce cooling costs
Informed
Model and predict system behavior
Prevent, Detect, Recover

10. TARP: Evaluation Methodology
7 racks/row
40 servers/rack
150W idle
285W at 100%
25C
4 CRAC units
90 KW/CRAC
Flovent – CFD Simulator
Validated in [Sharma03]
Gives Tin and Tout for each object
Tsup = 15 + (Tred – max(Tin))

11. Minimize Heat Recirculation
2-phase calibration creates power budgets
Baseline workload measures Qb and δQb
I.e., all servers on but idle
Bin servers into non-overlapping pods
Utilize each pod 100%; re-measure Q and δQ
Heat Recirculation Factor (HRF)
HRFj = (Qj – Qb) / (δQj – δQb)