Single event upsets (SEUs) are a threat to any computing system running on hardware that has not been physically radiation hardened. In addition to mandating the use of performance- limited, hardened heritage equipment, prior techniques for dealing with the SEU problem often involved hardware- based error detection and correction (EDAC). With limited computing resources, software-based EDAC, or any more elaborate recovery methods, were often not feasible. Synthetic aperture radars (SARs), when operated in the space environment, are interesting due to their relevance to NASAs objectives, but problematic in the sense of producing prodigious amounts of “raw” data. Prior implementations of the SAR data processing algorithm have been too slow, too computationally intensive, and require too much application memory for onboard execution to be a realistic option when using the type of heritage processing technology described above.

This standard C-language implementation of SAR data processing is distributed over many cores of a Tilera Multicore Processor, and employs novel Radiation Hardening by Software (RHBS) techniques designed to protect the component processes (one per core) and their shared application memory from the sort of SEUs expected in the space environment. The source code includes calls to Tilera APIs, and a specialized Tilera compiler is required to produce a Tilera executable. The compiled application reads input data describing the position and orientation of a radar platform, as well as its radar-burst data, over time and writes out processed data in a form that is useful for analysis of the radar observations.

The application is capable of recovering from some types of SEU-induced interference with component processes and/or corruption of the shared application memory, and also writes out performance statistics designed to assist in evaluating the effectiveness of the novel RHBS techniques employed. These performance data are useful in identifying, time-stamping, and (indirectly) geolocating SEU incidents along with the application’s responses.

The tileSAR software distributes the problem of processing SAR data over an “engine” made up of a number of cooperating parallel processes (one per core). This engine is replicated three times within the Tilera processor; always one process per core, and all engines running in parallel. Each engine also includes an additional scrubbing process (core), and there is one final triple-voting process external to the engines. When distributing the SAR algorithm among the processes of each engine, the usual single-stringed implementation (each sub-task executed in sequence) is replaced with an implementation where independent operations are carried out concurrently by independent processes. Every opportunity for concurrency within this algorithm is exploited, as this dramatically reduces execution time. The result of each engine’s processing is a series of output records. The processes that make up each engine share a single working set of data, collectively called the engine’s “workspace.” The state of each workspace at each synchronization point is expected to be identical to that of the other engines, and reflects the state of progress the engine has made through its execution of the algorithm. The combined effect of scrubbing and triple-voting enables certain types of workspace corruption to be detected and corrected such that processing may continue without interruption or error.

This work was done by Matthew Holland of Goddard Space Flight Center. GSC-15757-1

NASA Tech Briefs Magazine

This article first appeared in the November, 2011 issue of NASA Tech Briefs Magazine.

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