time-critical computing: some insights and implications professor jan jonsson department of computer...

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Time-Critical Computing: Time-Critical Computing: Some Insights and Implications Some Insights and Implications Professor Jan Jonsson Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

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Page 1: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

Time-Critical Computing:Time-Critical Computing:Some Insights and ImplicationsSome Insights and Implications

Professor Jan JonssonProfessor Jan Jonsson

Department of Computer Science and EngineeringChalmers University of Technology

Page 2: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

Future systems execute reliable, high-throughput applications with explicit real-time constraints.

Scientific contextScientific context

The availability of computer systems with attractive The availability of computer systems with attractive price-performance ratios has enabled:price-performance ratios has enabled:

Low-cost nodes in distributed real-time systems Powerful telecommunication/multimedia servers

Future systems execute reliablereliable, high-throughputhigh-throughput applications with explicit real-timereal-time constraints.

Multi-core processor nodes in embedded systems

Page 3: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

Scientific contextScientific context

Low-cost, multi-core nodes in distributed real-time systems

Page 4: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

Two research directions in time-critical computing:Two research directions in time-critical computing:

Optimal resource allocation– Goals: maximize system performance (e.g. timing guarantees,

reliability, throughput); minimize resource usage (e.g. power consumption, size, weight)

– Challenges: multi-objective optimization; time-complexity

Efficient on-line scheduling– Goal: improve performance on multiprocessor systems

(e.g. scheduling techniques for uniprocessors are inefficient)– Challenge: circumvent fundamental theoretical limitations

(e.g. hybrid scheduling techniques are needed)

ChallengesChallenges

Page 5: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

1. Power-Aware Scheduling of Time-Critical Tasks:1. Power-Aware Scheduling of Time-Critical Tasks:

[1998] I. Hong, G. Qu, M. Potkonjak and M. Srivastava. "Synthesis Techniques for Low-Power Hard Real-Time Systems on Variable Voltage Processors”

[2004] H. Aydin, R. Melhem, D. Mossé, and P. Mejia-Alvarez. "Power-Aware Scheduling for Periodic Real-Time Tasks”

[2013] M. Bambagini, J. Lelli, G. Buttazzo, and G. Lipari. "On the energy-aware partitioning of real-time tasks on homogeneous multi-processor systems”

TopicsTopics

Page 6: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

2. Scheduling of Time-Critical Tasks on Multiprocessors:2. Scheduling of Time-Critical Tasks on Multiprocessors:

[2001] B. Andersson, S. Baruah and J. Jonsson. "Static-Priority Scheduling on Multiprocessors"

[2005] Baker, T.P. "An analysis of EDF schedulability on a multiprocessor"

[2009] K. Lakshmanan, R. Rajkumar, and J. Lehoczky. “Partitioned fixed-priority preemptive scheduling for multi-core processors”

TopicsTopics

Page 7: Time-Critical Computing: Some Insights and Implications Professor Jan Jonsson Department of Computer Science and Engineering Chalmers University of Technology

End of lectureEnd of lecture