A review of High Performance Computing foundations for scientists

The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [1, 2]. Simulation enables the evaluation of quantities which otherwise would not be accessible, helps to improve experiments and provides new insights on systems which are analysed [3-6]. Knowing the fundamentals of computation can be very useful for scientists, for it can help them to improve the performance of their theoretical models and simulations. This review includes some technical essentials that can be useful to this end, and it is devised as a complement for researchers whose education is focused on scientific issues and not on technological respects. In this document we attempt to discuss the fundamentals of High Performance Computing (HPC) [7] in a way which is easy to understand without much previous background. We sketch the way standard computers and supercomputers work, as well as discuss distributed computing and discuss essential aspects to take into account when running scientific calculations in computers.Comment: 33 page

A parallel Heap-Cell Method for Eikonal equations

Numerous applications of Eikonal equations prompted the development of many efficient numerical algorithms. The Heap-Cell Method (HCM) is a recent serial two-scale technique that has been shown to have advantages over other serial state-of-the-art solvers for a wide range of problems. This paper presents a parallelization of HCM for a shared memory architecture. The numerical experiments in $R^3$ show that the parallel HCM exhibits good algorithmic behavior and scales well, resulting in a very fast and practical solver. We further explore the influence on performance and scaling of data precision, early termination criteria, and the hardware architecture. A shorter version of this manuscript (omitting these more detailed tests) has been submitted to SIAM Journal on Scientific Computing in 2012.Comment: (a minor update to address the reviewers' comments) 31 pages; 15 figures; this is an expanded version of a paper accepted by SIAM Journal on Scientific Computin

Time-Dependent Density-Functional Theory in Massively Parallel Computer Architectures: The Octopus Project

Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn–Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn–Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures.Chemistry and Chemical Biolog

Alignment of helical membrane protein sequences using AlignMe

Few sequence alignment methods have been designed specifically for integral membrane proteins, even though these important proteins have distinct evolutionary and structural properties that might affect their alignments. Existing approaches typically consider membrane-related information either by using membrane-specific substitution matrices or by assigning distinct penalties for gap creation in transmembrane and non-transmembrane regions. Here, we ask whether favoring matching of predicted transmembrane segments within a standard dynamic programming algorithm can improve the accuracy of pairwise membrane protein sequence alignments. We tested various strategies using a specifically designed program called AlignMe. An updated set of homologous membrane protein structures, called HOMEP2, was used as a reference for optimizing the gap penalties. The best of the membrane-protein optimized approaches were then tested on an independent reference set of membrane protein sequence alignments from the BAliBASE collection. When secondary structure (S) matching was combined with evolutionary information (using a position-specific substitution matrix (P)), in an approach we called AlignMePS, the resultant pairwise alignments were typically among the most accurate over a broad range of sequence similarities when compared to available methods. Matching transmembrane predictions (T), in addition to evolutionary information, and secondary-structure predictions, in an approach called AlignMePST, generally reduces the accuracy of the alignments of closely-related proteins in the BAliBASE set relative to AlignMePS, but may be useful in cases of extremely distantly related proteins for which sequence information is less informative. The open source AlignMe code is available at https://sourceforge.net/projects/alignme​/, and at http://www.forrestlab.org, along with an online server and the HOMEP2 data set

The Design of a System Architecture for Mobile Multimedia Computers

This chapter discusses the system architecture of a portable computer, called Mobile Digital Companion, which provides support for handling multimedia applications energy efficiently. Because battery life is limited and battery weight is an important factor for the size and the weight of the Mobile Digital Companion, energy management plays a crucial role in the architecture. As the Companion must remain usable in a variety of environments, it has to be flexible and adaptable to various operating conditions. The Mobile Digital Companion has an unconventional architecture that saves energy by using system decomposition at different levels of the architecture and exploits locality of reference with dedicated, optimised modules. The approach is based on dedicated functionality and the extensive use of energy reduction techniques at all levels of system design. The system has an architecture with a general-purpose processor accompanied by a set of heterogeneous autonomous programmable modules, each providing an energy efficient implementation of dedicated tasks. A reconfigurable internal communication network switch exploits locality of reference and eliminates wasteful data copies

Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers

This paper improves state-of-the-art visual object trackers that use online adaptation. Our core contribution is an offline meta-learning-based method to adjust the initial deep networks used in online adaptation-based tracking. The meta learning is driven by the goal of deep networks that can quickly be adapted to robustly model a particular target in future frames. Ideally the resulting models focus on features that are useful for future frames, and avoid overfitting to background clutter, small parts of the target, or noise. By enforcing a small number of update iterations during meta-learning, the resulting networks train significantly faster. We demonstrate this approach on top of the high performance tracking approaches: tracking-by-detection based MDNet and the correlation based CREST. Experimental results on standard benchmarks, OTB2015 and VOT2016, show that our meta-learned versions of both trackers improve speed, accuracy, and robustness.Comment: Code: https://github.com/silverbottlep/meta_tracker

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light-matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials)

Optimisation of the first principle code Octopus for massive parallel architectures: application to light harvesting complexes

[EN]: Computer simulation has become a powerful technique for assisting scientists in developing novel insights into the basic phenomena underlying a wide variety of complex physical systems. The work reported in this thesis is concerned with the use of massively parallel computers to simulate the fundamental features at the electronic structure level that control the initial stages of harvesting and transfer of solar energy in green plants which initiate the photosynthetic process. Currently available supercomputer facilities offer the possibility of using hundred of thousands of computing cores. However, obtaining a linear speed-up from HPC systems is far from trivial. Thus, great efforts must be devoted to understand the nature of the scientific code, the methods of parallel execution, data communication requirements in multi-process calculations, the efficient use of available memory, etc. This thesis deals with all of these themes, with a clear objective in mind: the electronic structure simulation of complete macro-molecular complexes, namely the Light Harvesting Complex II, with the aim of understanding its physical behaviour. In order to simulate this complex, we have used (with the assistance of the PRACE consortium) some of the most powerful supercomputers in Europe to run Octopus, a scientific software package for Density Functional Theory and TimeDependent Density Functional Theory calculations. Results obtained with Octopus have been analysed in depth in order to identify the main obstacles to optimal scaling using thousands of cores. Many problems have emerged, mainly the poor performance of the Poisson solver, high memory requirements, the transfer of high quantities of complex data structures among processes, and so on. Finally, all of these problems have been overcome, and the new version reaches a very high performance in massively parallel systems. Tests run efficiently up to 128K processors and thus we have been able to complete the largest TDDFT calculations performed to date. At the conclusion of this work it has been possible to study the Light Harvesting Complex II as originally envisioned.[EU]: Konputagailu bidezko simulazioa da, gaur egun, zientzialariek eskura duten tresnarik ahaltsuenetako bat sistema fisiko konplexuen portaera ulertzen saiatzeko. Oinarrizko fenomeno fisiko horiek simulatzeko superkonputagailuak erabili dira tesi honetan aurkezten den lanean. Konkretuki, punta-puntako konputagailuak erabili dira fotosintesiaren lehen urratsak ulertzeko, landare berdeetan eguzki-energiaren xurgatze-prozesua kontrolatzen duen molekula simulatuz. Superkonputazio-zentroek ehunka milaka prozesatze-nukleo dituzten makinak erabiltzeko aukera eskaintzen dute, baina ez da batere erraza azelerazio-faktore linealak lortzea halako konputagailuetan. Hori dela eta, ahalegin handiak egin behar dira, informatikaren ikuspegitik, sistema osoaren ezagutza ahalik eta sakonena lortzeko: kode zientifikoen izaera, beraren exekuzio paraleloen aukerak, prozesuen arteko datu-transmisioaren beharrak, sistemaren memoriaren erabilera eraginkorrena, eta abar. Tesi honek aurreko arazo guztiei aurre egiten die, helburu argi batekin: konplexu makromolekular osoen simulazioa, konkretuki Light Harvesting Complex II sistemaren egitura elektronikoaren simulazioa, beraren portaera fisikoa ulertu ahal izateko. Sistema hori simulatu ahal izateko bidean, Europako superkonputagailu azkarrenak erabili dira (PRACE partzuergoari esker) Octopus software-paketea exekutatzeko, zeina Density Functional Theory eta Time-Dependent Density Functional Theory izeneko teorien araberako simulazio elektronikoak egiten baititu. Lortutako emaitzak sakonki analizatu dira, milaka konputazio-nukleo eraginkorki erabiltzea oztopatzen zuten arazoak aurkitzeko. Problema ugari azaldu dira bide horretan, nagusiki Poisson ebazlearen errendimendu baxua, memoria eskaera handiak, datu-egitura konplexuen kopuru handiko transferentziak, eta abar. Azkenean, problema horiek guztiak ebatzi dira, eta bertsio berriak errendimendu handia lortu du superkonputagailu paraleloetan. Exekuzio eraginkorrak frogatu ahal izan ditugu 128K prozesadorera arte eta, ondorioz, inoizko TDDFT simulaziorik handienak egin ahal izan ditugu. Hala, lan honen amaieran, hasierako helburua bete ahal izan da: Light Harvesting Complex II sistema molekularraren azterketa egitea.University of the Basque Country, UPV/EHU, University of Coimbra, Red Española de Supercomputación (RES), Jülich Supercomputing Centre (JSC), Rechenzentrum Garching, Cineca, Barcelona Supercomputing Center (BSC), CeSViMa, European Research Council Advanced Grant DYNamo (ERC-2010-AdG-267374), Spanish Grant (FIS2013-46159-C3-1-P), Grupos Consolidados UPV/EHU del Gobierno Vasco (IT578-13), Grupos Consolidados UPV/EHU del Gobierno Vasco (IT395-10), European Community FP7 project CRONOS (Grant number 280879-2), COST Actions CM1204 (XLIC) and MP1306 (EUSpec), ALDAPA research group belongs to the Basque Advanced Informatics Laboratory (BAILab) supported by the University of the Basque Country UPV/EHU (grant UFI11/45).Peer Reviewe