The application of fault signature analysis in Tenaga Nasional Berhad Malaysia

Unplanned electrical power outages are a major concern to power utilities throughout the whole world. Unfortunately, power outages will continue to occur and they cannot be fully prevented. It could be the result of lightning strikes, tree encroachment, or equipment failure. However, the impact can be reduced if power system operators are equipped with the appropriate tools to analyze the root cause of the failure. Without sufficient tools to identify the nature of a fault, the restoration process could be delayed because the operator does not know whether it is safe to normalize the isolated line. This paper describes the new and simplified fault signature analysis approach on Tenaga Nasional Berhad using a digital fault recorder. The research focuses on the contribution of the lightning strike and tree encroachment to the overhead line tripping in Malaysi

Efficient fault tolerance for selected scientific computing algorithms on heterogeneous and approximate computer architectures

Scientific computing and simulation technology play an essential role to solve central challenges in science and engineering. The high computational power of heterogeneous computer architectures allows to accelerate applications in these domains, which are often dominated by compute-intensive mathematical tasks. Scientific, economic and political decision processes increasingly rely on such applications and therefore induce a strong demand to compute correct and trustworthy results. However, the continued semiconductor technology scaling increasingly imposes serious threats to the reliability and efficiency of upcoming devices. Different reliability threats can cause crashes or erroneous results without indication. Software-based fault tolerance techniques can protect algorithmic tasks by adding appropriate operations to detect and correct errors at runtime. Major challenges are induced by the runtime overhead of such operations and by rounding errors in floating-point arithmetic that can cause false positives. The end of Dennard scaling induces central challenges to further increase the compute efficiency between semiconductor technology generations. Approximate computing exploits the inherent error resilience of different applications to achieve efficiency gains with respect to, for instance, power, energy, and execution times. However, scientific applications often induce strict accuracy requirements which require careful utilization of approximation techniques. This thesis provides fault tolerance and approximate computing methods that enable the reliable and efficient execution of linear algebra operations and Conjugate Gradient solvers using heterogeneous and approximate computer architectures. The presented fault tolerance techniques detect and correct errors at runtime with low runtime overhead and high error coverage. At the same time, these fault tolerance techniques are exploited to enable the execution of the Conjugate Gradient solvers on approximate hardware by monitoring the underlying error resilience while adjusting the approximation error accordingly. Besides, parameter evaluation and estimation methods are presented that determine the computational efficiency of application executions on approximate hardware. An extensive experimental evaluation shows the efficiency and efficacy of the presented methods with respect to the runtime overhead to detect and correct errors, the error coverage as well as the achieved energy reduction in executing the Conjugate Gradient solvers on approximate hardware