Daniele Cesini
(INFN - CNAF)
25/02/16, 11:00
The embedded and high-performance computing sectors have in the past been very isolated and unaware of each other’s needs and technologies. Similar isolations have occurred between HPC and the mobile/tablets commodity markets. We are now experiencing a very important convergence between markets, both in constraints and needs as well as in technologies. High computational demands, power...
Enrico Calore
(UNIFE and INFN)
25/02/16, 11:30
Energy efficiency is quickly gaining importance in the HPC field.
High-end processors are evolving towards more advanced power-saving and power-monitoring technologies, while low-power processors, designed for the mobile market, are gaining interest in the HPC area thanks to their increasing computing capabilities, in conjunction with their competitive pricing.
On the other hand, from the...
Denis Bastieri
(UNIPD and INFN)
25/02/16, 12:30
Gamma-Ray Astronomy is an optimal test-ground for Low-Power Computing and High-Throughput Computing. On the one hand, ground based detectors for Gamma-ray Astronomy are the prototypes for distributed experiments, as single detectors may be scattered in an area of few square kilometres, and the capability of each unit to process, at least partially, its own data before sending them to the...
Luca Benini
(ETHZ and UNIBO)
25/02/16, 14:00
The “internet of everything” envisions trillions of connected objects loaded with high-bandwidth sensors requiring massive amounts of local signal processing, fusion, pattern extraction and classification. Higher level intelligence, requiring local storage and complex search and matching algorithms, will come next. From the computational viewpoint, the challenge is formidable and can be...
Daniele Tafani
(Leibniz Supercomputing Center)
25/02/16, 14:30
Due to rising energy prices and increasing carbon footprint, it is commonly accepted that the main constraint for future, sustainable many-Peta to Exascale HPC system will be dictated by power consumption. Along with the design of more energy-efficient hardware and cooling infrastructures, a viable way of addressing this challenge is offered by energy-aware scheduling. This presentation...
Lasse Natvig
(Norwegian University of Science and Technology)
25/02/16, 15:00
Climbing Mont Blanc (CMB) is an open online judge used for training in energy efficient programming of state-of-the-art heterogeneous multicores. It is based on an Odroid-XU3 board with an Exynos Octa processor and integrated power sensors. The system currently accepts C and C++ programs, with support for OpenCL v1.1, OpenMP 4.0 and Pthreads. Programs submitted using the graphical user...
David Abdurachmanov
(CERN)
25/02/16, 17:30
Overview of various efforts at Compact Muon Solenoid (CMS) experiment at CERN on emerging general-purpose computing platforms for High Throughput Computing (HTC). We report our experience on software porting, performance, energy efficiency and building a demonstrator Worldwide LHC Computing Grid (WLCG) Tier-3 computing site at Princeton University based on ARMv8 64-bit Server-on-Chip.
Pinaki Kumar
(Technische Universiteit Eindhoven)
26/02/16, 09:00
In this contribution we will discuss issues related to the optimisation of Lattice Boltzmann multicomponent flow solver to study the physics of soft glassy system on multi-GPU platforms.
Roberto De Pietri
(UNIPR and INFN)
26/02/16, 10:00
Low-Power architectures are subject of much interest also as viable alternatives to traditional HPC platform. In this talk we will focus on
the performance that can now be obtained porting a large simulation toolkit (The EinsteinToolkit), widely used in Numerical Astrophysics
to simulated matter coupled to the Einstein’s equations, to Low Power Architectures. We considered multicores / multi...
Felice Pantaleo
(CERN)
26/02/16, 11:00
This presentation will focus on our first-hand experience in running benchmarks using Open Source OpenCL, Beignet, on both the GPU and CPU of a low power Intel Skylake SoC.
Filippo Spiga
26/02/16, 11:30
The presentation is going to be focused on the first-hand experience in running CUDA-accelerated applications on ARM64 platforms with NVIDIA GPU Kepler cards. The talk will underline challenges, difficulties, weakness and strength of an heterogeneous platform.
