Techniques for Multicore Thermal Management: Classification and New Exploration
By James Mc Donald, Margaret Martonosi. International Symposium on Computer Architecture, 2006
444 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Hardware and Architecture
View Paper: https://www.semanticscholar.org/paper/82a7484f34ac13267facbfa73d3b3e4b6e6fc86d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Carole-Jean Wu
- Canturk Isci
- Sarma B. K. Vrudhula
- Benjamin Gaudette
- Parthasarathy Ranganathan
- Ramya Raghavendra
- Zhikui Wang
- Vanish Talwar
In Hardware and Architecture
- Carole-Jean Wu
- Canturk Isci
- Sarma B. K. Vrudhula
- Benjamin Gaudette
- Parthasarathy Ranganathan
- Zhikui Wang
- Xiaoyun Zhu
- Ramya Raghavendra
Citations in the corpus
- Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approach (2008, background): “At the chip level, the work on multicore thermal management [24] tries to achieve thermal management through changing voltage or migrating process among multiple cores.”
- Improving smartphone user experience by balancing performance and energy with probabilistic QoS guarantee (2016, background): “We summarize some of the most closely related works to this paper [7, 10, 12, 13, 16, 18, 20–24, 26, 27, 36, 38, 43, 44, 47, 52].”
- Dynamo: Facebook's Data Center-Wide Power Management System (2016, background): “Most prior work focused on server-level [8], [9], [10] or ensemble-level [4] power management.”
- No "power" struggles: coordinated multi-level power management for the data center (2008, methodology): “Second, using our unified architecture as the base, we perform a detailed quantitative sensitivity analysis and draw conclusions about the impact of different architectures, implementations, workloads, and system design choices.”
- An Analysis of Efficient Multi-Core Global Power Management Policies: Maximizing Performance for a Given Power Budget (2006, background): “Prior research in this area has been primarily limited to studying the efficacy of providing dynamic management of power and thermal hot spots through localized responses provided at the core-level [2, 11] or through global scheduling heuristics [7, 22, 37].”