Clusters, Clouds, and Grids are three different computational paradigms with the intent or potential to support High Performance Computing (HPC). Currently, they consist of hardware, management, and usage models particular to different computational regimes, e.g., highperformance cluster systems designed to support tightly coupledscientific simulation codes typically utilize high-speed interconnects and commercial cloud systems designed to support software as a service (SAS) do not. However, in order to support HPC, all must at least utilize large numbers of resources and hence effective HPC in any of these paradigms must address the issue of resiliency at large-scale.
Recent trends in high-performance computing (HPC) systems have clearly indicated that future increases in performance, in excess of those resulting from improvements in single-processor performance, will be achieved through corresponding increases in system scale, i.e., using a significantly larger component count. As the raw computational performance of the world's fastest HPC systems increases from today's current multi-petascale to next-generation exascale capability and beyond, their number of computational, networking, and storage components will grow from the ten-to-one-hundred thousand compute nodes of today's systems to several hundreds of thousands of compute nodes in the foreseeable future. This substantial growth in system scale, and the resulting component count, poses a challenge for HPC system and application software with respect to reliability, availability and serviceability (RAS).
The expected total component count of these HPC systems calls into questions many of today's HPC RAS assumptions. Although the mean-time to failure (MTTF) for each individual component, e.g., processor, memory module, and network interface, may be above typical consumer product standard, the probability of failure for the overall system scales proportionally to the number of interdependent components and their combined probabilities of failure. Thus, the enormous number of individual components results in a much lower system meantime to failure (SMTTF), causing more frequent system-wide interruptions than displayed by current HPC systems. This effect is not limited to hardware components, but also extends to software components, e.g., operating system, system software, and applications. Although software components do not show less reliability with increasing age like hardware components, they do contain other sources of failures, such as design and implementation errors. Furthermore, the health of software components also involves resource utilization, such as processor, memory and network usage.
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