@conference {17887,
	title = {Comparing the Performance of High-Level Middleware Systems in Shared and Distributed Memory Parallel Environments},
	booktitle = {Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International},
	year = {2005},
	month = {2005/04//},
	pages = {30 - 30},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The utilization of toolkits for writing parallel and/or distributed applications has been shown to greatly enhance developer{\textquoteright}s productivity. Such an approach hides many of the complexities associated with writing these applications, rather than relying solely on programming language aids and parallel library support, such as MPI or PVM. In this work, we evaluate three different middleware systems that have been used to implement a computation and I/O-intensive data analysis application from the domain of computer vision. This study shows the benefits and overheads associated with each of the middleware systems, in different homogeneous computational environments and with different workloads. Our results lead the way toward being able to make better decisions for tuning the application environment, for selecting the appropriate middleware, and also for designing more powerful middleware systems to efficiently build and run highly complex applications in both parallel and distributed computing environments.},
	keywords = {Application software, Computer science, Computer vision, Data analysis, Distributed computing, distributed computing environment, distributed memory parallel environment, distributed shared memory systems, Educational institutions, high-level middleware system, I/O-intensive data analysis application, Libraries, Middleware, parallel computing environment, parallel library support, parallel memories, programming language, programming languages, Runtime environment, shared memory parallel environment, Writing},
	isbn = {0-7695-2312-9},
	doi = {10.1109/IPDPS.2005.144},
	author = {Kim,Jik-Soo and Andrade,H. and Sussman, Alan}
}
@article {14770,
	title = {Critical path profiling of message passing and shared-memory programs},
	journal = {IEEE Transactions on Parallel and Distributed Systems},
	volume = {9},
	year = {1998},
	month = {1998/10//},
	pages = {1029 - 1040},
	abstract = {We introduce a runtime, nontrace-based algorithm to compute the critical path profile of the execution of message passing and shared-memory parallel programs. Our algorithm permits starting or stopping the critical path computation during program execution and reporting intermediate values. We also present an online algorithm to compute a variant of critical path, called critical path zeroing, that measures the reduction in application execution time that improving a selected procedure will have. Finally, we present a brief case study to quantify the runtime overhead of our algorithm and to show that online critical path profiling can be used to find program bottlenecks},
	keywords = {Computer Society, Concurrent computing, critical path computation, critical path profile, critical path zeroing, distributed processing, distributed shared memory systems, Instruments, Message passing, Monitoring, online algorithm, online critical path profiling, Parallel algorithms, program bottlenecks, Runtime, runtime nontrace-based algorithm, runtime overhead, shared-memory programs, system monitoring, Time measurement, Yarn},
	isbn = {1045-9219},
	doi = {10.1109/71.730530},
	author = {Hollingsworth, Jeffrey K}
}
