New challenges in Astronomy and Astrophysics (AA) are urging the need for many exceptionally computationally intensive simulations. “Exascale” (and beyond) computational facilities are mandatory to address the size of theoretical problems and data coming from the new generation of observational facilities in AA. Currently, the High-Performance Computing (HPC) sector is undergoing a profound phase of innovation, in which the primary challenge to the achievement of the “Exascale” is the power consumption. The goal of this work is to give some insights about performance and energy footprint of contemporary architectures for a real astrophysical application in an HPC context. We use a state-of-the-art N-body application that we re-engineered and optimized to exploit the heterogeneous underlying hardware fully. We quantitatively evaluate the impact of computation on energy consumption when running on four different platforms. Two of them represent the current HPC systems (Intel-based and equipped with NVIDIA GPUs), one is a micro-cluster based on ARM-MPSoC, and one is a “prototype towards Exascale” equipped with ARM-MPSoCs tightly coupled with FPGAs. We investigate the behavior of the different devices where the high-end GPUs excel in terms of time-to-solution while MPSoC-FPGA systems outperform GPUs in power consumption. Our experience reveals that considering FPGAs for computationally intensive application seems very promising, as their performance is improving to meet the requirements of scientific applications. This work can be a reference for future platform development for astrophysics applications where computationally intensive calculations are required.

Modern Grid middleware is built around components providing basic functionality, such as data storage, authentication, security, job management, resource monitoring and reservation. In this paper we describe the Computing Resource Execution and Management (CREAM) service. CREAM provides a Web service-based job execution and management capability for Grid systems; in particular, it is being used within the gLite middleware. CREAM exposes a Web service interface allowing conforming clients to submit and manage computational jobs to a Local Resource Management System. We developed a special component, called ICE (Interface to CREAM Environment) to integrate CREAM in gLite. ICE transfers job submissions and cancellations from the Workload Management System, allowing users to manage CREAM jobs from the gLite User Interface. This paper describes some recent studies aimed at assessing the performance and reliability of CREAM and ICE; those tests have been performed as part of the acceptance tests for integration of CREAM and ICE in gLite. We also discuss recent work towards enhancing CREAM with a BES and JSDL compliant interface.

INAF Trieste Astronomical Observatory (OATs) has a long tradition in information technology applied to Astronomical and Astrophysical use cases, particularly for what regards computing for data reduction, analysis and simulations; data and archives management; space missions data processing; design and software development for ground-based instruments. The ensemble of these activities, in the last years, pushed the need to acquire new computing resources and technologies and to deep competences in theirs management. In this paper we describe INAF-OATs computing centre technological stuff, our involvement in different EU Projects both in the path of building of EOSC, the European Open Science Cloud; in the design and prototyping of new Exascale supercomputers in Europe and the main research activities carried on using our computing centre.