A Survey of Prediction and Classification Techniques in Multicore Processor Systems

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems

Dynamic Thermal and Power Management: From Computers to Buildings

Thermal and power management have become increasingly important for both computing and physical systems. Computing systems from real-time embedded systems to data centers require effective thermal and power management to prevent overheating and save energy. In the mean time, as a major consumer of energy buildings face challenges to reduce the energy consumption for air conditioning while maintaining comfort of occupants. In this dissertation we investigate dynamic thermal and power management for computer systems and buildings. (1) We present thermal control under utilization bound (TCUB), a novel control-theoretic thermal management algorithm designed for single core real-time embedded systems. A salient feature of TCUB is to maintain both desired processor temperature and real-time performance. (2) To address unique challenges posed by multicore processors, we develop the real-time multicore thermal control (RT-MTC) algorithm. RT-MTC employs a feedback control loop to enforce the desired temperature and CPU utilization of the multicore platform via dynamic frequency and voltage scaling. (3) We research dynamic thermal management for real-time services running on server clusters. We develop the control-theoretic thermal balancing (CTB) to dynamically balance temperature of servers via distributing clients\u27 service requests to servers. Next, (4) we propose CloudPowerCap, a power cap management system for virtualized cloud computing infrastructure. The novelty of CloudPowerCap lies in an integrated approach to coordinate power budget management and resource management in a cloud computing environment. Finally we expand our research to physical environment by exploring several fundamental problems of thermal and power management on buildings. We analyze spatial and temporal data acquired from an real-world auditorium instrumented by a multi-modal sensor network. We propose a data mining technique to determine the appropriate number and location of temperature sensors for estimating the spatiotemporal temperature distribution of the auditorium. Furthermore, we explore the potential energy savings that can be achieved through occupancy-based HVAC scheduling based on real occupancy data of the auditorium

A dynamic power-aware partitioner with task migration for multicore embedded systems

Nowadays, a key design issue in embedded systems is how to reduce the power consumption, since batteries have a limited energy budget. For this purpose, several techniques such as Dynamic Voltage Scaling (DVS) or task migration can be used. DVS allows reducing power by selecting the optimal voltage supply, while task migration achieves this effect by balancing the workload among cores. This paper first analyzes the impact on energy due to task migration in multicore embedded systems with DVS capability and using the well-known Worst Fit (WF) partitioning heuristic. To reduce overhead, migrations are only performed at the time that a task arrives to and/or leaves the system and, in such a case, only one migration is allowed. The huge potential on energy saving due to task migration, leads us to propose a new dynamic partitioner, namely DP, that migrates tasks in a more efficient way than typical partitioners. Unlike WF, the proposed algorithm examines which is the optimal target core before allowing a migration. Experimental results show that DP can improve energy consumption in a factor up to 2.74 over the typical WF algorithm. © 2011 Springer-Verlag.This work was supported by Spanish CICYT under Grant TIN2009-14475-C04-01, and by Consolider-Ingenio under Grant CSD2006-00046.March Cabrelles, JL.; Sahuquillo Borrás, J.; Petit Martí, SV.; Hassan Mohamed, H.; Duato Marín, JF. (2011). A dynamic power-aware partitioner with task migration for multicore embedded systems. En Euro-Par 2011 Parallel Processing. Springer Verlag (Germany). 2011(6852):218-229. https://doi.org/10.1007/978-3-642-23400-2_21S21822920116852AlEnawy, T.A., Aydin, H.: Energy-Aware Task Allocation for Rate Monotonic Scheduling. In: Proceedings of the 11th Real Time on Embedded Technology and Applications Symposium, March 7-10, pp. 213–223. IEEE Computer Society, San Francisco (2005)Aydin, H., Yang, Q.: Energy-Aware Partitioning for Multiprocessor Real-Time Systems. In: Proceedings of the 17th International Parallel and Distributed Processing Symposium, Workshop on Parallel and Distributed Real-Time Systems, April 22-26, p. 113. IEEE Computer Society, Nice (2003)Baker, T.P.: An Analysis of EDF schedulability on a multiprocessor. IEEE Transactions on Parallel and Distributed Systems 16(8), 760–768 (2005)Brandenburg, B.B., Calandrino, J.M., Anderson, J.H.: On the Scalability of Real-Time Scheduling Algorithms on Multicore Platforms: A Case Study. In: Proceedings of the 29th Real-Time Systems Symposium, November 30-December 3, pp. 157–169. IEEE Computer Society, Barcelona (2008)Brião, E., Barcelos, D., Wronski, F., Wagner, F.R.: Impact of Task Migration in NoC-based MPSoCs for Soft Real-time Applications. In: Proceedings of the International Conference on VLSI, October 15-17, pp. 296–299. IEEE Computer Society, Atlanta (2007)Cazorla, F., Knijnenburg, P., Sakellariou, R., Fernández, E., Ramirez, A., Valero, M.: Predictable Performance in SMT Processors: Synergy between the OS and SMTs. IEEE Transactions on Computers 55(7), 785–799 (2006)Donald, J., Martonosi, M.: Techniques for Multicore Thermal Management: Classification and New Exploration. In: Proceedings of the 33rd Annual International Symposium on Computer Architecture, June 17-21, pp. 78–88. IEEE Computer Society, Boston (2006)El-Haj-Mahmoud, A., AL-Zawawi, A., Anantaraman, A., Rotenberg, E.: Virtual Multiprocessor: An Analyzable, High-Performance Architecture for Real-Time Computing. In: Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems, September 24-27, pp. 213–224. ACM Press, San Francisco (2005)Hung, C., Chen, J., Kuo, T.: Energy-Efficient Real-Time Task Scheduling for a DVS System with a Non-DVS Processing Element. In: Proceedings of the 27th Real-Time Systems Symposium, December 5-8, pp. 303–312. IEEE Computer Society, Rio de Janeiro (2006)Kalla, R., Sinharoy, B., Tendler, J.M.: IBM Power5 Chip: A Dual-Core Multithreaded Processor. IEEE Micro 24(2), 40–47 (2004)Kato, S., Yamasaki, N.: Global EDF-based Scheduling with Efficient Priority Promotion. In: Proceedings of the 14th International Conference on Embedded and Real-Time Computing Systems and Applications, August 25-27, pp. 197–206. IEEE Computer Society, Kaohisung (2008)Malardalen Real-Time Research Center, Vasteras, Sweden: WCET Analysis Project. WCET Benchmark Programs (2006), [Online], http://www.mrtc.mdh.se/projects/wcet/March, J., Sahuquillo, J., Hassan, H., Petit, S., Duato, J.: A New Energy-Aware Dynamic Task Set Partitioning Algorithm for Soft and Hard Embedded Real-Time Systems. To be published on The Computer Journal (2011)McNairy, C., Bhatia, R.: Montecito: A Dual-Core, Dual-Thread Itanium Processor. IEEE Micro 25(2), 10–20 (2005)Seo, E., Jeong, J., Park, S., Lee, J.: Energy Efficient Scheduling of Real-Time Tasks on Multicore Processors. IEEE Transactions on Parallel and Distributed Systems 19(11), 1540–1552 (2008)Shah, A.: Arm plans to add multithreading to chip design. ITworld (2010), [Online], http://www.itworld.com/hardware/122383/arm-plans-add-multithreading-chip-designUbal, R., Sahuquillo, J., Petit, S., López, P.: Multi2Sim: A Simulation Framework to Evaluate Multicore-Multithreaded Processors. In: Proceedings of the 19th International Symposium on Computer Architecture and High Performance Computing, October 24-27, pp. 62–68. IEEE Computer Society, Gramado (2007)Watanabe, R., Kondo, M., Imai, M., Nakamura, H., Nanya, T.: Task Scheduling under Performance Constraints for Reducing the Energy Consumption of the GALS Multi-Processor SoC. In: Proceedings of the Design Automation and Test in Europe, April 16-20, pp. 797–802. ACM, Nice (2007)Wei, Y., Yang, C., Kuo, T., Hung, S.: Energy-Efficient Real-Time Scheduling of Multimedia Tasks on Multi-Core Processors. In: Proceedings of the 25th Symposium on Applied Computing, March 22-26, pp. 258–262. ACM, Sierre (2010)Wu, Q., Martonosi, M., Clark, D.W., Reddi, V.J., Connors, D., Wu, Y., Lee, J., Brooks, D.: A Dynamic Compilation Framework for Controlling Microprocessor Energy and Performance. In: Proceedings of the 38th Annual IEEE/ACM International Symposium on Microarchitecture, November 12-16, pp. 271–282. IEEE Computer Society, Barcelona (2005)Zheng, L.: A Task Migration Constrained Energy-Efficient Scheduling Algorithm for Multiprocessor Real-time Systems. In: Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing, September 21-25, pp. 3055–3058. IEEE Computer Society, Shanghai (2007

Radiation safety based on the sky shine effect in reactor

In the reactor operation, neutrons and gamma rays are the most dominant radiation. As protection, lead and concrete shields are built around the reactor. However, the radiation can penetrate the water shielding inside the reactor pool. This incident leads to the occurrence of sky shine where a physical phenomenon of nuclear radiation sources was transmitted panoramic that extends to the environment. The effect of this phenomenon is caused by the fallout radiation into the surrounding area which causes the radiation dose to increase. High doses of exposure cause a person to have stochastic effects or deterministic effects. Therefore, this study was conducted to measure the radiation dose from sky shine effect that scattered around the reactor at different distances and different height above the reactor platform. In this paper, the analysis of the radiation dose of sky shine effect was measured using the experimental metho

Task Activity Vectors: A Novel Metric for Temperature-Aware and Energy-Efficient Scheduling

This thesis introduces the abstraction of the task activity vector to characterize applications by the processor resources they utilize. Based on activity vectors, the thesis introduces scheduling policies for improving the temperature distribution on the processor chip and for increasing energy efficiency by reducing the contention for shared resources of multicore and multithreaded processors

Power Management Techniques for Data Centers: A Survey

With growing use of internet and exponential growth in amount of data to be stored and processed (known as 'big data'), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power consumption of the data centers. For this reason, managing power consumption of data centers has become essential. In this paper, we highlight the need of achieving energy efficiency in data centers and survey several recent architectural techniques designed for power management of data centers. We also present a classification of these techniques based on their characteristics. This paper aims to provide insights into the techniques for improving energy efficiency of data centers and encourage the designers to invent novel solutions for managing the large power dissipation of data centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy Efficiency, Green Computing, DVFS, Server Consolidatio

A Power-Aware Framework for Executing Streaming Programs on Networks-on-Chip

Nilesh Karavadara, Simon Folie, Michael Zolda, Vu Thien Nga Nguyen, Raimund Kirner, 'A Power-Aware Framework for Executing Streaming Programs on Networks-on-Chip'. Paper presented at the Int'l Workshop on Performance, Power and Predictability of Many-Core Embedded Systems (3PMCES'14), Dresden, Germany, 24-28 March 2014.Software developers are discovering that practices which have successfully served single-core platforms for decades do no longer work for multi-cores. Stream processing is a parallel execution model that is well-suited for architectures with multiple computational elements that are connected by a network. We propose a power-aware streaming execution layer for network-on-chip architectures that addresses the energy constraints of embedded devices. Our proof-of-concept implementation targets the Intel SCC processor, which connects 48 cores via a network-on- chip. We motivate our design decisions and describe the status of our implementation