68 research outputs found
The Crossover between Liquid and Solid Electron Phases in Quantum Dots: A Large-Scale Configuration-Interaction Study
We study the crossover between liquid and solid electron phases in a
two-dimensional harmonic trap as the density is progressively diluted. We infer
the formation of geometrically ordered phases from charge distributions and
pair correlation functions obtained via a large scale configuration interaction
calculation.Comment: LaTeX 2e, Elsevier style. Four pages, two b/w postscript figures.
Submitted to Computer Physics Communications as a proceeding of Conference on
Computational Physics, Genova 200
Continuous Learning of HPC Infrastructure Models using Big Data Analytics and In-Memory processing Tools
open4siThis work was supported, in parts, by the FP7 ERC Advance project MULTITHERMAN (g.a. 291125), by the EU H2020 FETHPC project ANTAREX (g.a. 67623) and by the EU H2020 FETHPC project Exanode (g.a. 671578).Exascale computing represents the next leap in the HPC race. Reaching this level of performance is subject to several engineering challenges such as energy consumption, equipment-cooling, reliability and massive parallelism. Model-based optimization is an essential tool in the design process and control of energy efficient, reliable and thermally constrained systems. However, in the Exascale domain, model learning techniques tailored to the specific supercomputer require real measurements and must therefore handle and analyze a massive amount of data coming from the HPC monitoring infrastructure. This becomes rapidly a 'big data' scale problem. The common approach where measurements are first stored in large databases and then processed is no more affordable due to the increasingly storage costs and lack of real-time support. Nowadays instead, cloud-based machine learning techniques aim to build on-line models using real-time approaches such as 'stream processing' and 'in-memory' computing, that avoid storage costs and enable fastdata processing. Moreover, the fast delivery and adaptation of the models to the quick data variations, make the decision stage of the optimization loop more effective and reliable. In this paper we leverage scalable, lightweight and flexible IoT technologies, such as the MQTT protocol, to build a highly scalable HPC monitoring infrastructure able to handle the massive sensor data produced by next-gen HPC components. We then show how state-of-the art tools for big data computing and analysis, such as Apache Spark, can be used to manage the huge amount of data delivered by the monitoring layer and to build adaptive models in real-time using on-line machine learning techniques.openBeneventi, Francesco; Bartolini, Andrea; Cavazzoni, Carlo; Benini, LucaBeneventi, Francesco; Bartolini, Andrea; Cavazzoni, Carlo; Benini, Luc
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Electronic and Transport Properties of Artificial Gold Chains
Article on electronic and transport properties of artificial gold chains
Performance analysis and optimization of the FFTXlib on the Intel knights landing architecture
In this paper, we address the decreasing performance of the FFTXlib, the Fast Fourier Transformation (FFT) kernel of Quantum ESPRESSO, when scaling to a full KNL node. An increased performance in the FFTXlib will likewise increase the performance of the entire Quantum ESPRESSO code one of the most used plane-wave DFT codes in the community of material science. Our approach focuses on, first, overlapping computation and communication and, second, decreasing resource contention for higher compute efficiency. In order to achieve this we use the OmpSs programming model based on task dependencies. We allow overlapping of computation and communication by converting all steps of the FFT into tasks following a flow dependency. In the same way, we decrease resource contention by converting each FFT into an individual task that can be scheduled asynchronously. In both cases, multiple FFTs can be computed in parallel. The task-based optimizations are implemented in the FFTXlib and show up to 10% runtime reduction on the already highly optimized version. Since the task scheduling is done dynamically during execution by the parallel runtime, not statically by the user, it also frees the user from finding the ideal parallel configuration himself.We gratefully acknowledge the support of the MaX and POP projects, which have received funding from the European Union’s Horizon 2020 research and innovation programme
under grant agreement No. 676598 and 676553, respectively.Peer ReviewedPostprint (author's final draft
User Plane Function Offloading in P4 switches for enhanced 5G Mobile Edge Computing
This demo shows a 5G X-haul testbed enhanced with P4 switches implementing the offloading of the User Plane Function module. The P4 code includes GTP protocol encapsulation/decapsulation function, fully configurable N3-N6-N9 steering, and advanced online monitoring of the experienced latency metadata
Full configuration interaction approach to the few-electron problem in artificial atoms
We present a new high-performance configuration interaction code optimally
designed for the calculation of the lowest energy eigenstates of a few
electrons in semiconductor quantum dots (also called artificial atoms) in the
strong interaction regime. The implementation relies on a single-particle
representation, but it is independent of the choice of the single-particle
basis and, therefore, of the details of the device and configuration of
external fields. Assuming no truncation of the Fock space of Slater
determinants generated from the chosen single-particle basis, the code may
tackle regimes where Coulomb interaction very effectively mixes many
determinants. Typical strongly correlated systems lead to very large
diagonalization problems; in our implementation, the secular equation is
reduced to its minimal rank by exploiting the symmetry of the effective-mass
interacting Hamiltonian, including square total spin. The resulting Hamiltonian
is diagonalized via parallel implementation of the Lanczos algorithm. The code
gives access to both wave functions and energies of first excited states.
Excellent code scalability in a parallel environment is demonstrated; accuracy
is tested for the case of up to eight electrons confined in a two-dimensional
harmonic trap as the density is progressively diluted and correlation becomes
dominant. Comparison with previous Quantum Monte Carlo simulations in the
Wigner regime demonstrates power and flexibility of the method.Comment: RevTeX 4.0, 18 pages, 6 tables, 9 postscript b/w figures. Final
version with new material. Section 6 on the excitation spectrum has been
added. Some material has been moved to two appendices, which appear in the
EPAPS web depository in the published versio
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