@conference {14803,
	title = {Performance Measurement of Novice HPC Programmers Code},
	booktitle = {Proceedings of the 3rd International Workshop on Software Engineering for High Performance Computing Applications},
	series = {SE-HPC {\textquoteright}07},
	year = {2007},
	month = {2007///},
	pages = {3{\textendash} - 3{\textendash}},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	abstract = {Performance is one of the key factors of improving productivity in High Performance Computing (HPC). In this paper we discuss current studies in the field of performance measurement of codes captured in classroom experiments for the High Productivity Computing Project (HPCS). We give two examples of measurements introducing two new hypotheses: spending more effort doesn{\textquoteright}t always result in improvement of performance for novices; the use of higher level MPI functions promises better performance for novices. We also present a tool - the Automated Performance Measurement System (APMS). APMS helps to partially automate the measurement of the performance of a set of parallel programs with several inputs. The design and implementation of the tool is flexible enough to allow other researchers to conduct similar studies.},
	keywords = {measurement, performance, performance measures, product metrics, program analysis},
	isbn = {0-7695-2969-0},
	doi = {http://dx.doi.org/10.1109/SE-HPC.2007.4},
	url = {http://dx.doi.org/10.1109/SE-HPC.2007.4},
	author = {Alameh, Rola and Zazworka, Nico and Hollingsworth, Jeffrey K}
}
@conference {14760,
	title = {Dynamic program instrumentation for scalable performance tools},
	booktitle = {Scalable High-Performance Computing Conference, 1994., Proceedings of the},
	year = {1994},
	month = {1994/05//},
	pages = {841 - 850},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Presents a new technique called {\textquoteleft}dynamic instrumentation{\textquoteright} that provides efficient, scalable, yet detailed data collection for large-scale parallel applications. Our approach is unique because it defers inserting any instrumentation until the application is in execution. We can insert or change instrumentation at any time during execution by modifying the application{\textquoteright}s binary image. Only the instrumentation required for the currently selected analysis or visualization is inserted. As a result, our technique collects several orders of magnitude less data than traditional data collection approaches. We have implemented a prototype of our dynamic instrumentation on the CM-5, and present results for several real applications. In addition, we include recommendations to operating system designers, compiler writers, and computer architects about the features necessary to permit efficient monitoring of large-scale parallel systems},
	keywords = {Application software, binary image, compiler writing, Computer architecture, Computer displays, Computerized monitoring, Concurrent computing, data acquisition, data collection, data visualisation, Data visualization, dynamic program instrumentation, efficient monitoring, executing program, Instruments, large-scale parallel applications, Large-scale systems, operating system design, Operating systems, parallel programming, program analysis, program diagnostics, program visualization, Programming profession, Sampling methods, scalable performance tools, software tools},
	isbn = {0-8186-5680-8},
	doi = {10.1109/SHPCC.1994.296728},
	author = {Hollingsworth, Jeffrey K and Miller, B. P and Cargille, J.}
}
