NERSC 2016: Extreme Computation and Data for Science 1

Overview By the year 2016, scientific computing will see a continued exponential increase in computational power. Simulations at or near exascale level will be conceivable in a growing number of scientific frontiers. HPC facilities in 2016 will be dealing with an exponential increase in experimental and simulation data. Scientific discovery will increasingly be based on the creation, maintenance, and analysis of exa-to zetabyte data repositories that need to be stored, accessed, analyzed, processed, shared, and understood. Analytics (the techniques and technology in data analysis, visualization, analytics, networking, and collaboration tools) will be essential in datarich scientific applications. As DOE's Keystone high performance computing and stroage facility with the mission to accelerate the pace of scientific discovery by providing high performance computing, information, data, and communications resources for all open applied and basic science and engineering sponsored by the DOE Office of Science, NERSC 2016 will provide unique resources and assistance to the open science community to enable community members to make effective use of exascale HPC resources and data. To meet the computational challenge, NERSC will field a series of early production systems that increase performance for science. To meet the data challenges, NERSC envisions hosting community data repositories with integrated information management and analytics tools and services, as well as new exascale storage technologies. To meet the ever increasing electrical power demands of ultra scale computers NERSC will explore new, tightly coupled hardware/software designs that emulate the achievements of the low-power embedded computing market to result in computers that meet the computational needs of scientific applications while showing a dramatic increase in energy efficiency. This paper describes NERSC's approach to achieving this vision for two if the three areas -Computing and Data. NERSC's approach to ultra efficient computing is documented in other papers 1 and not discussed further here. NERSC Computational Services The Keystone Facility The need for increases in computational resources between today and 2016 is well documented in the DOE Greenbook, 2 the SCaLeS Report, 3 and the E3 Report

Modeling the sorption dynamics of NaH using a reactive force field

We have parametrized a reactive force field for NaH, ReaxFFNaH, against a training set of ab initio derived data. To ascertain that ReaxFFNaH is properly parametrized, a comparison between ab initio heats of formation of small representative NaH clusters with ReaxFFNaH was done. The results and trend of ReaxFFNaH are found to be consistent with ab initio values. Further validation includes comparing the equations of state of condensed phases of Na and NaH as calculated from ab initio and ReaxFFNaH. There is a good match between the two results, showing that ReaxFFNaH is correctly parametrized by the ab initio training set. ReaxFFNaH has been used to study the dynamics of hydrogen desorption in NaH particles. We find that ReaxFFNaH properly describes the surface molecular hydrogen charge transfer during the abstraction process. Results on heat of desorption versus cluster size shows that there is a strong dependence on the heat of desorption on the particle size, which implies that nanostructuring enhances desorption process. To gain more insight into the structural transformations of NaH during thermal decomposition, we performed a heating run in a molecular dynamics simulation. These runs exhibit a series of drops in potential energy, associated with cluster fragmentation and desorption of molecular hydrogen. This is consistent with experimental evidence that NaH dissociates at its melting point into smaller fragments

Predictions of melting, crystallization, and local atomic arrangements of aluminum clusters using a reactive force field

A parametrized reactive force field model for aluminum ReaxFFAl has been developed based on density functional theory (DFT) data. A comparison has been made between DFT and ReaxFFAl outputs to ascertain whether ReaxFFAl is properly parametrized and to check if the output of the latter has correlation with DFT results. Further checks include comparing the equations of state of condensed phases of Al as calculated from DFT and ReaxFFAl. There is a good match between the two results, again showing that ReaxFFAl is correctly parametrized as per the DFT input. Simulated annealing has been performed on aluminum clusters Aln using ReaxFFAl to find the stable isomers of the clusters. A plot of stability function versus cluster size shows the existence of highly stable clusters (magic clusters). Quantum mechanically these magic clusters arise due to the complete filling of the orbital shells. However, since force fields do not care about electrons but work on the assumption of validity of Born–Oppenheimer approximation, the magic clusters are therefore correlated with high structural symmetry. There is a rapid decline in surface energy contribution due to the triangulated nature of the surface atoms leading to higher coordination number. The bulk binding energy is computed to be 76.8 kcal/mol. This gives confidence in the suitability of ReaxFF for studying and understanding the underlying dynamics in aluminum clusters. In the quantification of the growth of cluster it is seen that as the size of the clusters increase there is preference for the coexistence of fcc/hcp orders at the expense of simple icosahedral ordering, although there is some contribution from distorted icosahedral ordering. It is found that even for aluminum clusters with 512 atoms distorted icosahedral ordering exists. For clusters with N≥256 atoms fcc ordering dominates, which implies that at this point we are already on the threshold of bulklike bonding

Parametrization of a reactive force field for aluminum hydride

A reactive force field, REAXFF, for aluminum hydride has been developed based on density functional theory (DFT) derived data. REAXFF_(AlH_3) is used to study the dynamics governing hydrogen desorption in AlH_3. During the abstraction process of surface molecular hydrogen charge transfer is found to be well described by REAXFF_(AlH_3). Results on heat of desorption versus cluster size show that there is a strong dependence of the heat of desorption on the particle size, which implies that nanostructuring enhances desorption process. In the gas phase, it was observed that small alane clusters agglomerated into a bigger cluster. After agglomeration molecular hydrogen was desorbed from the structure. This thermodynamically driven spontaneous agglomeration followed by desorption of molecular hydrogen provides a mechanism on how mobile alane clusters can facilitate the mass transport of aluminum atoms during the thermal decomposition of NaAlH_4

Modeling of Hydrogen Storage Materials: A Reactive Force Field for NaH

Parameterization of a reactive force field for NaH is done using ab initio derived data. The parameterized force field(ReaxFFNaH) is used to study the dynamics governing hydrogen desorption in NaH. During the abstraction process of surface molecular hydrogen charge transfer is found to be well described by the parameterized force field. To gain more insight into the mechanism governing structural transformation of NaH during thermal decomposition a heating run in a molecular dynamics simulation is done. The result shows that a clear signature of hydrogen desorption is the fall in potential energy surface during heating

Multiscale modeling of interaction of alane clusters on Al(111) surfaces: A reactive force field and infrared absorption spectroscopy approach

We have used reactive force field (ReaxFF) to investigate the mechanism of interaction of alanes on Al(111) surface. Our simulations show that, on the Al(111) surface, alanes oligomerize into larger alanes. In addition, from our simulations, adsorption of atomic hydrogen on Al(111) surface leads to the formation of alanes via H-induced etching of aluminum atoms from the surface. The alanes then agglomerate at the step edges forming stringlike conformations. The identification of these stringlike intermediates as a precursor to the bulk hydride phase allows us to explain the loss of resolution in surface IR experiments with increasing hydrogen coverage on single crystal Al(111) surface. This is in excellent agreement with the experimental works of Go et al. [ E. Go, K. Thuermer, and J. E. Reutt-Robey, Surf. Sci. 437, 377 (1999) ]. The mobility of alanes molecules has been studied using molecular dynamics and it is found that the migration energy barrier of Al_(2)H_6 is 2.99 kcal/mol while the prefactor is D_0 = 2.82 × 10^(−3) cm^2/s. We further investigated the interaction between an alane and an aluminum vacancy using classical molecular dynamics simulations. We found that a vacancy acts as a trap for alane, and eventually fractionates/annihilates it. These results show that ReaxFF can be used, in conjunction with ab initio methods, to study complex reactions on surfaces at both ambient and elevated temperature conditions

Processing liquid metal for conformable electronics

Future generations of robots, electronics, and assistive medical devices will include systems that are soft, elastically deformable, and may adapt their functionality in unstructured environments. This will require soft active materials for power circuits and sensing of deformation and contact pressure. Liquid-embedded elastomer electronics offer one solution as key elements of highly deformable and soft robotic systems. Several designs for stretchable conductors and soft sensory skins (including strain, pressure, and curvature sensors) based on a liquid-embedded-elastomer approach have been developed. Many of these fluid–elastomer composites utilize liquid metal alloys due to their high conductivities and inherent compliance. Understanding how these alloys can be processed for high-yield manufacturability is critical to the development of parallel processing technology, which is needed to create more complex and low-cost systems. This discussion will highlight surface interactions between droplets of gallium–indium alloys and elastomeric substrates, and the implementation of this study to selective patterning, direct-writing, and inkjet printing of hyperelastic electronic components

BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery

We present a novel computational framework that connects Blue Waters, the NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science Grid technology. To enable this computational infrastructure, we configured, for the first time, a LIGO Data Grid Tier-1 Center that can submit heterogeneous LIGO workflows using Open Science Grid facilities. In order to enable a seamless connection between the LIGO Data Grid and Blue Waters via Open Science Grid, we utilize Shifter to containerize LIGO's workflow software. This work represents the first time Open Science Grid, Shifter, and Blue Waters are unified to tackle a scientific problem and, in particular, it is the first time a framework of this nature is used in the context of large scale gravitational wave data analysis. This new framework has been used in the last several weeks of LIGO's second discovery campaign to run the most computationally demanding gravitational wave search workflows on Blue Waters, and accelerate discovery in the emergent field of gravitational wave astrophysics. We discuss the implications of this novel framework for a wider ecosystem of Higher Performance Computing users.Comment: 10 pages, 10 figures. Accepted as a Full Research Paper to the 13th IEEE International Conference on eScienc

Bostonia: The Boston University Alumni Magazine. Volume 9

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs