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A concurrent test architecture for massively parallel computers and its error detection capability

机译:大规模并行计算机的并发测试体系结构及其错误检测功能

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Presents new principles for online monitoring in the context of multiprocessors (especially massively parallel processors) and then focuses on the effect of the aliasing probability on the error detection process. In the proposed test architecture, concurrent testing (or online monitoring) at the system level is accomplished by enforcing the run-time testing of the data and control dependences of the algorithm currently being executed on the parallel computer. In order to help in this process, each message contains both source and destination addresses. At each message source, the sequence of destination addresses of the outgoing messages is compressed on a block basis. At the same time, at each destination, the sequence of source addresses of all incoming messages is compressed, also on a block basis. Concurrent compression of the instructions executed by the PEs is also possible. As a result of this procedure, an image of the data dependences and of the control flow of the currently running algorithm is created. This image is compared, at the end of each computational block, with a reference image created at compilation time. The main results of this work are in proposing new principles for the online system-level testing of multiprocessor systems, based on signaturing and monitoring the data dependences together with the control dependences, and in providing an analytical model and analysis for the address compression process used for monitoring the data routing process.
机译:提出了在多处理器(尤其是大规模并行处理器)环境中进行在线监视的新原理,然后重点介绍了混叠概率对错误检测过程的影响。在提出的测试体系结构中,通过强制执行数据的运行时测试以及对并行计算机上当前正在执行的算法的控制依赖性,可以在系统级别进行并发测试(或在线监视)。为了帮助完成此过程,每条消息均包含源地址和目标地址。在每个消息源处,传出消息的目标地址序列都按块进行压缩。同时,在每个目标位置,所有传入消息的源地址序列也按块进行压缩。 PE并发压缩指令也是可能的。作为该过程的结果,创建了数据依存关系和当前运行算法的控制流的图像。在每个计算块的末尾,将此图像与在编译时创建的参考图像进行比较。这项工作的主要结果是为多处理器系统的在线系统级测试提出新的原理,该方法基于对数据依赖性以及控制依赖性进行签名和监视,并为使用的地址压缩过程提供分析模型和分析。用于监视数据路由过程。

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