SEEC: A Framework for Self-aware Management of Multicore Resources
Name
MIT-CSAIL-TR-2011-016.pdf
Size
1.13 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Hoffmann, Henry
Maggio, Martina
Santambrogio, Marco D.
Leva, Alberto
Agarwal, Anant
Advisor(s)
Anant Agarwal
Date Issued
March 24, 2011
Series/Report no.
MIT-CSAIL-TR-2011-016
Abstract
This paper presents SEEC, a self-aware programming model, designed to reduce programming effort in modern multicore systems. In the SEEC model, application programmers specify application goals and progress, while systems programmers separately specify actions system software and hardware can take to affect an application (e.g. resource allocation). The SEEC runtime monitors applications and dynamically selects actions to meet application goals optimally (e.g. meeting performance while minimizing power consumption). The SEEC runtime optimizes system behavior for the application rather than requiring the application programmer to optimize for the system. This paper presents a detailed discussion of the SEEC model and runtime as well as several case studies demonstrating their benefits. SEEC is shown to optimize performance per Watt for a video encoder, find optimal resource allocation for an application with complex resource usage, and maintain the goals of multiple applications in the face of environmental fluctuations.
Subjects
Self-adaptive, self-optimizing, self-tuning, self-*, power-aware
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