Astrophysical code migration into Exascale Era

The ExaNeSt and EuroExa H2020 EU-funded projects aim to design and develop an exascale ready computing platform prototype based on low-energy-consumption ARM64 cores and FPGA accelerators. We participate in the application-driven design of the hardware solutions and prototype validation. To carry on this work we are using, among others, Hy-Nbody, a state-of-the-art direct N-body code. Core algorithms of Hy-Nbody have been improved in such a way to increasingly fit them to the exascale target platform. Waiting for the ExaNest prototype release, we are performing tests and code tuning operations on an ARM64 SoC facility: a SLURM managed HPC cluster based on 64-bit ARMv8 Cortex-A72/Cortex-A53 core design and powered by a Mali-T864 embedded GPU. In parallel, we are porting a kernel of Hy-Nbody on FPGA aiming to test and compare the performance-per-watt of our algorithms on different platforms. In this paper we describe how we re-engineered the application and we show first results on ARM SoC.Comment: 4 pages, 1 figure, 1 table; proceedings of ADASS XXVIII, accepted by ASP Conference Serie

Simulating realistic disk galaxies with a novel sub-resolution ISM model

We present results of cosmological simulations of disk galaxies carried out with the GADGET-3 TreePM+SPH code, where star formation and stellar feedback are described using our MUlti Phase Particle Integrator (MUPPI) model. This description is based on simple multi-phase model of the interstellar medium at unresolved scales, where mass and energy flows among the components are explicitly followed by solving a system of ordinary differential equations. Thermal energy from SNe is injected into the local hot phase, so as to avoid that it is promptly radiated away. A kinetic feedback prescription generates the massive outflows needed to avoid the over-production of stars. We use two sets of zoomed-in initial conditions of isolated cosmological halos with masses (2-3) * 10^{12} Msun, both available at several resolution levels. In all cases we obtain spiral galaxies with small bulge-over-total stellar mass ratios (B/T \approx 0.2), extended stellar and gas disks, flat rotation curves and realistic values of stellar masses. Gas profiles are relatively flat, molecular gas is found to dominate at the centre of galaxies, with star formation rates following the observed Schmidt-Kennicutt relation. Stars kinematically belonging to the bulge form early, while disk stars show a clear inside-out formation pattern and mostly form after redshift z=2. However, the baryon conversion efficiencies in our simulations differ from the relation given by Moster et al. (2010) at a 3 sigma level, thus indicating that our stellar disks are still too massive for the Dark Matter halo in which they reside. Results are found to be remarkably stable against resolution. This further demonstrates the feasibility of carrying out simulations producing a realistic population of galaxies within representative cosmological volumes, at a relatively modest resolution.Comment: 19 pages, 21 figures, MNRAS accepte

HYDRODYNAMICAL SIMULATIONS OF GALAXY CLUSTERS: THERMODYNAMICS AND CHEMICAL ENRICHMENT

2002/2003XVI Ciclo1975Versione digitalizzata della tesi di dottorato cartacea

Numerical evaluation of heat transfer effects on the improvement of efficiency of a spark ignition engine characterized by cylinder variability

In this work, the effects of in-cylinder heat transfer on indicated thermal efficiency of a spark ignition engine showing a cylinder-to-cylinder variation are numerically analyzed. A 1D CFD model of engine is developed and integrated with a turbulent combustion sub-model and with a refined thermal sub-model for cylinders and exhaust pipes. The model is validated against the engine measurements. Thermal sub-model includes a Finite Element (FE) approach to predict the temperatures of cylinders and of exhaust pipes. The model correctly reproduces the thermodynamic behavior of cylinders at varying the operating condition. Simulations at low load and speed indicate that in-cylinder heat transfer represents a relevant percentage on total fuel energy entering the cylinder. Therefore, heat transfer exerts an important influence on the improvement of engine indicated thermal efficiency when considering the sole combustion phasing optimization of cylinders and the suppression of cylinder-to-cylinder variation

GrGadget: an N-body TreePM relativistic code for cosmological simulations

We present the merging of the Particle-Mesh (PM) relativistic Gevolution code with the TreePM Gadget-4 code, with the aim of studying general relativity effects in cosmology. Our code, called GrGadget, is able to track the evolution of metric perturbations in the weak field limit by using Gevolution's implementation of a relativistic PM in the Poisson gauge. To achieve this, starting from Gevolution we have written a C++ library called libgevolution, that allows a code to access and use the same abstractions and resources that Gevolution uses for its PM-only N-body simulations. The code works under the assumption that particle interactions at short distances can be approximated as Newtonian, so that we can combine the forces computed with a Newtonian Tree with those computed with a relativistic PM. The result is a TreePM simulation code that represents metric perturbations at the scales where they are relevant, while resolving non-linear structures. We validate our code by closely matching Gadget-4 forces, computed with the Tree switched off, with those computed with libgevolution in the Newtonian limit. With GrGadget we obtain a matter power spectrum that is compatible with Newtonian Gadget at small scales and contains GR features at large scales that are consistent with results obtained with Gevolution. We demonstrate that, due to the better resolution of the highly non-linear regime, the representation of the relativistic fields sampled on the mesh improves with respect to the PM-only simulations.Comment: 15 pages, 14 figure

On the dynamical origin of the ICM metallicity evolution

We present a study on the origin of the metallicity evolution of the intra-cluster medium (ICM) by applying a semi-analytic model of galaxy formation to N-body/smoothed particle hydrodynamic (SPH) non-radiative numerical simulations of clusters of galaxies. The semi-analytic model includes gas cooling, star formation, supernovae feedback and metal enrichment, and is linked to the diffuse gas of the underlying simulations so that the chemical properties of gas particles are dynamically and consistently generated from stars in the galaxies. This hybrid model lets us have information on the spatial distribution of metals in the ICM. The results obtained for a set of clusters with virial masses of ∼1.5 × 1015 h−1 M contribute to the theoretical interpretation of recent observational X-ray data, which indicate a decrease of the average iron content of the intra-cluster gas with increasing redshift. We find that this evolution arises mainly as a result of a progressive increase of the iron abundance within ∼0.15 Rvir. The clusters have been considerably enriched by z ∼ 1 with very low contribution from recent star formation. Low entropy gas that has been enriched at high redshift sinks to the cluster centre contributing to the evolution of the metallicity profiles.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat

On the dynamical origin of the ICM metallicity evolution

We present a study on the origin of the metallicity evolution of the intra-cluster medium (ICM) by applying a semi-analytic model of galaxy formation to N-body/smoothed particle hydrodynamic (SPH) non-radiative numerical simulations of clusters of galaxies. The semi-analytic model includes gas cooling, star formation, supernovae feedback and metal enrichment, and is linked to the diffuse gas of the underlying simulations so that the chemical properties of gas particles are dynamically and consistently generated from stars in the galaxies. This hybrid model lets us have information on the spatial distribution of metals in the ICM. The results obtained for a set of clusters with virial masses of ∼1.5 × 1015 h−1 M contribute to the theoretical interpretation of recent observational X-ray data, which indicate a decrease of the average iron content of the intra-cluster gas with increasing redshift. We find that this evolution arises mainly as a result of a progressive increase of the iron abundance within ∼0.15 Rvir. The clusters have been considerably enriched by z ∼ 1 with very low contribution from recent star formation. Low entropy gas that has been enriched at high redshift sinks to the cluster centre contributing to the evolution of the metallicity profiles.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat

Chemical evolution of disc galaxies from cosmological simulations

We perform a suite of cosmological hydrodynamical simulations of disc galaxies, with zoomedin initial conditions leading to the formation of a halo of mass M-halo, DM similar or equal to 2 x 10(12) M-circle dot at redshift z = 0. These simulations aim at investigating the chemical evolution and the distribution of metals in a disc galaxy, and at quantifying the effect of (i) the assumed IMF, (ii) the adopted stellar yields, and (iii) the impact of binary systems originating SNe Ia on the process of chemical enrichment. We consider either a Kroupa, Tout & Gilmore (1993) or a more top-heavy Kroupa (2001) IMF, two sets of stellar yields and different values for the fraction of binary systems suitable to give rise to SNe Ia. We investigate stellar ages, SN rates, stellar and gas metallicity gradients, and stellar alpha-enhancement in simulations, and compare predictions with observations. We find that a Kroupa et al. (1993) IMF has to be preferred when modelling late-type galaxies in the local Universe. On the other hand, the comparison of stellar metallicity profiles and alpha-enhancement trends with observations of Milky Way stars shows a better agreement when a Kroupa (2001) IMF is assumed. Comparing the predicted SN rates and stellar alpha-enhancement with observations supports a value for the fraction of binary systems producing SNe Ia of 0.03, at least for late-type galaxies and for the considered IMFs. Adopted stellar yields are crucial in regulating cooling and star formation, and in determining patterns of chemical enrichment for stars, especially for those located in the galaxy bulge

Machine-learning method for quality of transmission prediction of unestablished lightpaths

Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of capital importance for an optimized design of optical networks. Due to the continuous advances in optical transmission, the number of design parameters available to system engineers (e.g., modulation formats, baud rate, code rate, etc.) is growing dramatically, thus significantly increasing the alternative scenarios for lightpath deployment. As of today, existing (pre-deployment) estimation techniques for lightpath QoT belong to two categories: "exact" analytical models estimating physical-layer impairments, which provide accurate results but incur heavy computational requirements, and margined formulas, which are computationally faster but typically introduce high link margins that lead to underutilization of network resources. In this paper, we explore a third option, i.e., machine learning (ML), as ML techniques have already been successfully applied for optimization and performance prediction of complex systems where analytical models are hard to derive and/ or numerical procedures impose high computational burden. We investigate a ML classifier that predicts whether the bit error rate of unestablished lightpaths meets the required system threshold based on traffic volume, desired route, and modulation format. The classifier is trained and tested on synthetic data and its performance is assessed over different network topologies and for various combinations of classification features. Results in terms of classifier accuracy are promising and motivate further investigation over real field data