A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach

Modern big data workflows are characterized by computationally intensive kernels. The simulated results are often combined with knowledge extracted from AI models to ultimately support decision-making. These energy-hungry workflows are increasingly executed in data centers with energy-efficient hardware accelerators since FPGAs are well-suited for this task due to their inherent parallelism. We present the H2020 project EVEREST, which has developed a system development kit (SDK) to simplify the creation of FPGA-accelerated kernels and manage the execution at runtime through a virtualization environment. This paper describes the main components of the EVEREST SDK and the benefits that can be achieved in our use cases.Comment: Accepted for presentation at DATE 2024 (multi-partner project session

Crack initiation and damage thresholds in some brittle metamorphic rock types

In this study 60 unconfined compression laboratory tests performed on three brittle metamorphic rock types were analysed in order to evaluate the stress thresholds associated with the onset of stable and unstable microcracking which are known in literature as the "crack initiation stress" and the "crack damage stress", respectively. The crack initiation stress was identified applying the lateral strain response (LSR) methodology while the crack damage stress was detected where total volumetric strain reversal occurs. Although the mineralogical and textural features were quite similar among the investigated rock types, the results of this study showed that the crack initiation and damage stress values were affected by variability. However, when the normalized stress values sci/sUCS and scd/sUCS were considered, the scatter in results decrease consistently suggesting that the stable and unstable crack growth begin at similar stress levels in the investigated rock types

Variability of intact rock mechanical properties for some metamorphic rock types and its implications on the number of test specimens

Intact rock strength and stiffness properties are commonly used in rock mass mechanical characterization, and their evaluation is usually based on laboratory tests. Due to the variability that affects strength and stiffness parameters, the determination of the number of laboratory- tested specimens required to obtain a reliable reference value is very useful. However, many studies reported in apposite literature focused only on the variability of strength parameters. This study investigates the variability of some of the most important strength and stiffness properties (unconfined compressive strength, indirect tensile strength, tangent and secant Young\u2019s moduli, Poisson\u2019s ratio) by applying statistical methods (statistical decision theory and statistical inference theory). A data set of 451 laboratory tests was used, performed on three rock types. The statistical analyses were applied with the aim of assessing how closely intact rock laboratory data follow a normal distribution and determining the minimum number of specimens required to obtain a reliable average value of the parameters in relation to a targeted precision index for a confidence level of 95 %. The results indicate that the minimum number of samples needed varies depending on rock and test types. Among the stiffness properties, tangent Young\u2019s modulus has a lower variability than both the secant modulus and the Poisson\u2019s ratio, whereas in terms of strength parameters, unconfined compressive strength is subject to greater variability than indirect tensile strength