TY - CONF T1 - Comparing the Performance of High-Level Middleware Systems in Shared and Distributed Memory Parallel Environments T2 - Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International Y1 - 2005 A1 - Kim,Jik-Soo A1 - Andrade,H. A1 - Sussman, Alan KW - Application software KW - Computer science KW - Computer vision KW - Data analysis KW - Distributed computing KW - distributed computing environment KW - distributed memory parallel environment KW - distributed shared memory systems KW - Educational institutions KW - high-level middleware system KW - I/O-intensive data analysis application KW - Libraries KW - Middleware KW - parallel computing environment KW - parallel library support KW - parallel memories KW - programming language KW - programming languages KW - Runtime environment KW - shared memory parallel environment KW - Writing AB - The utilization of toolkits for writing parallel and/or distributed applications has been shown to greatly enhance developer'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. JA - Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International PB - IEEE SN - 0-7695-2312-9 M3 - 10.1109/IPDPS.2005.144 ER - TY - JOUR T1 - Critical path profiling of message passing and shared-memory programs JF - IEEE Transactions on Parallel and Distributed Systems Y1 - 1998 A1 - Hollingsworth, Jeffrey K KW - Computer Society KW - Concurrent computing KW - critical path computation KW - critical path profile KW - critical path zeroing KW - distributed processing KW - distributed shared memory systems KW - Instruments KW - Message passing KW - Monitoring KW - online algorithm KW - online critical path profiling KW - Parallel algorithms KW - program bottlenecks KW - Runtime KW - runtime nontrace-based algorithm KW - runtime overhead KW - shared-memory programs KW - system monitoring KW - Time measurement KW - Yarn AB - 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 VL - 9 SN - 1045-9219 CP - 10 M3 - 10.1109/71.730530 ER -