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Diffstat (limited to 'content/preamble/abstract.tex')
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diff --git a/content/preamble/abstract.tex b/content/preamble/abstract.tex index 44fde95..c8078b4 100644 --- a/content/preamble/abstract.tex +++ b/content/preamble/abstract.tex @@ -1,4 +1,17 @@ \newpage \begin{center} - \bfseries\Huge Abstract + \bfseries\Huge Abstract \end{center} +In the modern AI economy, the strong computational demand causes datacenters to become complex, diverse facilities. +The sheer volume of CPUs, GPUs, NPUs \etc necessary to satisfy the customers' needs complicates system administration. +Moreover, future warehouses are at an even higher risk of becoming unmanageable, according to the Jevon's Paradox of Computer Systems. +To address this problem, the scientific community has proposed digital twinning as a datacenter management tool. +Digital Twins, which mirror complex objects and processes to provide actionable management improvements, are a novel way to tackle the rising warehouse complexity. +However, Datacenter Digital Twins are still under development, and lack crucial features, such as predictive analytics. +Without predictive maintenance and forecasts, system administrators cannot make well-informed operational decisions. + +In this work, we propose to enable predictive analytics for datacenters using digital twinning. +We survey the datacenter digital twinning field, and organize our findings into a system model. +Additionally, we design \mysystem~-- a novel reference architecture for predictive datacenter digital twins, and evaluate it through prototype-based experiments. +Our results indicate \mysystem is capable of reliably differentiating between mild and severe compute failures, and can successfully incorporate a predictive analytics engine to the benefit of datacenter managers. + |