Profile-driven selective program loading
作者： Tugrul Ince , Jeffrey K. Hollingsworth
DOI: 10.1007/978-3-642-15277-1_7
关键词: Paging 、 Computer science 、 Uniform memory access 、 Distributed memory 、 Shared memory 、 Operating system 、 Memory footprint 、 Data diffusion machine 、 Distributed shared memory 、 Distributed computing 、 Loader 、 Demand paging 、 Virtual memory 、 Memory management
摘要: Complex software systems use many shared libraries frequently composed of large off-the-shelf components. Only a limited number functions are used from these libraries. Historically demand paging prevented this wasting amounts memory. Many high end lack virtual memory and thus must load the entire library into each node's In paper we propose system which decreases footprint applications by selectively loading only portions After profiling executables libraries, our rewrites all target with new function ordering updated ELF program headers so that loader loads those likely to be given application includes fallback user-level recover in case failures analysis. We present study shows achieves more than 80% reduction pages loaded for several HPC while causing no performance overhead reasonably long running programs.
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