An Optimal Algorithm for Euclidean Shortest Paths in the Plane
SIAM Journal on Computing
A framework for dynamic energy efficiency and temperature management
Proceedings of the 33rd annual ACM/IEEE international symposium on Microarchitecture
Dynamic Thermal Management for High-Performance Microprocessors
HPCA '01 Proceedings of the 7th International Symposium on High-Performance Computer Architecture
Thermal-Aware Clustered Microarchitectures
ICCD '04 Proceedings of the IEEE International Conference on Computer Design
Balance of Power: Dynamic Thermal Management for Internet Data Centers
IEEE Internet Computing
Challenges of data center thermal management
IBM Journal of Research and Development - POWER5 and packaging
Making scheduling "cool": temperature-aware workload placement in data centers
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
ATC'07 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference
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An increasingly important requirement for energy-efficient data center operation is to diagnose and fix thermal anomalies that sometimes occur due to excessive workload or equipment failures. Today, the task of diagnosing thermal anomalies entails expert but tedious analysis of data collected manually from disparate management systems. Our ultimate goal is to substantially reduce the time, tedium and expertise required to diagnose thermal hotspots by developing a system that generates accurate diagnoses automatically. We describe a substantial step towards this goal: a loosely-coupled, semi-automated thermal diagnosis system that integrates IT and facilities data, uses simple heuristics to highlight the most likely culprits, and provides a graphical interface that enables an administrator to narrow the list further by exploring data correlations. Among the challenges addressed by our solution are coping with heterogeneous data types and data access methods, and detecting and managing erroneous sensor readings.