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Grizzaffi, Ann Marie

Publications and source records attributed to Grizzaffi, Ann Marie.

Fault-free performance validation of fault-tolerant multiprocessors

A validation methodology for testing the performance of fault-tolerant computer systems was developed and applied to the Fault-Tolerant Multiprocessor (FTMP) at NASA-Langley's AIRLAB facility. This methodology was claimed to be general enough to apply to any ultrareliable computer system. The goal of this research was to extend the validation methodology and to demonstrate the robustness of the validation methodology by its more extensive application to NASA's Fault-Tolerant Multiprocessor System (FTMP) and to the Software Implemented Fault-Tolerance (SIFT) Computer System. Furthermore, the performance of these two multiprocessors was compared by conducting similar experiments. An analysis of the results shows high level language instruction execution times for both SIFT and FTMP were consistent and predictable, with SIFT having greater throughput. At the operating system level, FTMP consumes 60% of the throughput for its real-time dispatcher and 5% on fault-handling tasks. In contrast, SIFT consumes 16% of its throughput for the dispatcher, but consumes 66% in fault-handling software overhead.

Czeck, Edward W.↗

Fault-free performance validation of avionic multiprocessors

This paper describes the application of a portion of a validation methodology to NASA's Fault-Tolerant Multiprocessor System (FTMP) and the Software Implemented Fault-Tolerance (SIFT) computer system. The methodology entails a building block approach, starting with simple baseline experiments and building to more complex experiments. The goal of the validation methodology is to thoroughly test and characterize the performance and behavior of ultrareliable computer systems. The validation methodology presented in this paper showed that the methodology is not machine specific and can be used in lieu of life testing approaches. By applying a building block approach at the systems level, the machine complexity was broken down to manageable levels independent of system implementation.

Czeck, Edward W.↗