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  1. Proceedings of the 4th Workshop on Power-Aware Computing and Systems (HotPower '11)
  2. SEEP: exploiting symbolic execution for energy-aware programming
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The interplay of software bloat, hardware energy proportionality and system bottlenecks
The case for sleep states in servers
Power-efficient networking for balanced system designs: early experiences with PCIe
SEEP: exploiting symbolic execution for energy-aware programming
Utilizing green energy prediction to schedule mixed batch and service jobs in data centers
Energy-aware writes to non-volatile main memory
Towards realizing a low cost and highly available datacenter power infrastructure
Leveraging thermal storage to cut the electricity bill for datacenter cooling
Ekho: bridging the gap between simulation and reality in tiny energy-harvesting sensors
Simultaneous multithreading on x86_64 systems: an energy efficiency evaluation

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SEEP: exploiting symbolic execution for energy-aware programming

Content Provider ACM Digital Library
Author Kapitza, Rüdiger Hönig, Timo Schröder-Preikschat, Wolfgang Eibel, Christopher
Abstract In recent years, there has been a rapid evolution of energy-aware computing systems (e.g., mobile devices, wireless sensor nodes), as still rising system complexity and increasing user demands make energy a permanently scarce resource. While static and dynamic optimizations for energy-aware execution have been massively explored, writing energy-efficient programs in the first place has only received limited attention. This paper proposes SEEP, a framework which exploits symbolic execution and platform-specific energy profiles to provide the basis for energy-aware programming. More specifically, the framework provides developers with information about the energy demand of their code at hand, even for the invocation of library functions and in settings with multiple possibly strongly heterogeneous target platforms. This equips developers with the necessary knowledge to take energy demand into account during the task of writing programs.
Starting Page 1
Ending Page 5
Page Count 5
File Format PDF
ISBN 9781450309813
DOI 10.1145/2039252.2039256
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-10-23
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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