LEONARDO: A Pan-European Pre-Exascale Supercomputer for HPC and AI Applications

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes the general architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution.Comment: 16 pages, 5 figures, 7 tables, to be published in Journal of Large Scale Research Facilitie

LEONARDO: A Pan-European Pre-Exascale Supercomputer for HPC and AI applications

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes thegeneral architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution

On the Origin of Metallicity and Stability of the Metastable Phase in Chemically Exfoliated MoS2_2

Chemical exfoliation of MoS$_2$ via Li-intercalation route has led to many desirable properties and spectacular applications due to the presence of a metastable state in addition to the stable H phase. However, the nature of the specific metastable phase formed, and its basic charge conduction properties have remained controversial. Using spatially resolved Raman spectroscopy (~1 micrometer resolution) and photoelectron spectroscopy (~120 nm resolution), we probe such chemically exfoliated MoS$_2$ samples in comparison to a mechanically exfoliated H phase sample and confirm that the dominant metastable state formed by this approach is a distorted T' state with a small semiconducting gap. Investigating two such samples with different extents of Li residues present, we establish that Li+ ions, not only help to exfoliate MoS$_2$ into few layer samples, but also contribute to enhancing the relative stability of the metastable state as well as dope the system with electrons, giving rise to a lightly doped small bandgap system with the T' structure, responsible for its spectacular properties.Comment: 34 pages, Main manuscript + Supplementary Materia

Improving Computational Efficiency for Energy Management Systems in Plug-in Hybrid Electric Vehicles Using Dynamic Programming Based Controllers

Reducing computational time has become a critical issue in recent years, particularly in the transportation field, where the complexity of scenarios demands lightweight controllers to run large simulations and gather results to study different behaviors. This study proposes two novel formulations of the Optimal Control Problem (OCP) for the Energy Management System of a Plug-in Hybrid Electric Vehicle (PHEV) and compares their performance with a benchmark found in the literature. Dynamic Programming was chosen as the optimization algorithm to solve the OCP in a Matlab environment, using the DynaProg toolbox. The objective is to address the optimality of the fuel economy solution and computational time. In order to improve the computational efficiency of the algorithm, an existing formulation from the literature was modified, which originally utilized three control inputs. The approach involves leveraging the unique equations that describe the Input-Split Hybrid powertrain, resulting in a reduction of control inputs firstly to two and finally to one in the proposed solutions. The aforementioned formulations are referred to as 2-Controls and a 1-Control. Virtual tests were conducted to evaluate the performance of the two formulations. The simulations were carried out in various scenarios, including urban and highway driving, to ensure the versatility of the controllers. The results demonstrate that both proposed formulations achieve a reduction in computational time compared to the benchmark. The 2-Controls formulation achieved a reduction in computational time of approximately 40 times, while the 1-Control formulation achieved a remarkable reduction of approximately 850 times. These reductions in computational time were achieved while obtaining a maximum difference in fuel economy of approximately 1.5% for the 1-Control formulation with respect to the benchmark solution. Overall, this study provides valuable insights into the development of efficient and optimal controllers for PHEVs, which can be applied to various transportation scenarios. The proposed formulations reduce computational time without sacrificing the optimality of the fuel economy solution, making them a promising approach for future research in this area

Association between metabolic syndrome, hypertension, and chronic depression: a postmenopausal women prevention study

Background. Chronic depression (CD) is common among postmenopausal women and is associated with an increased risk of cardiovascular disease (CVD). The diagnosis of CD is a challenging problem in clinical practice which is vastly underdiagnosed. CD detection in postmenopausal women with metabolic syndrome (MetS) or hypertension is necessary for CVD prevention. Our study aims to assess the prevalence of CD in postmenopausal women and the relationship between CD and MetS or hypertension. Results. The rate of CD was significantly higher among postmenopausal women with MetS compared with the control group [18% versus 8%; Odds ratio (OR) 2.2, P<0.007]. The CD rate was significantly higher among women with MetS and hypertension (21% versus 8%; OR 2.7, P<0.0000). The rate of CD was similar between women with MetS and women with hypertension, 18% versus 21%; OR 0.8, P<0.44) and between women with metabolic cardiomyopathy and hypertensive cardiomyopathy (10% versus 8%; OR 1.1, P<0.65). Conclusions. There is a relationship between MetS and CD, which is stronger when compared to women with hypertension. There is a need to improve the diagnosis of CD in postmenopausal women with MetS or hypertension as unrecognized and untreated CD is associated with a poor outcome