High Performance Computing Facilities Research Articles

High-resolution survey of tidal energy towards power generation and influence of sea-level-rise: A case study at coast of New Jersey, USA

Abstract The first and a crucial step in development of tidal power, which is now attracting more and more attention worldwide, is a reliable survey of temporal and spatial distribution of tidal energy along coastlines. This paper first reviews the advance in assessment of tidal energy, in particular marine hydrokinetic (MHK) energy, and discusses involved challenges and necessary approaches, and then it makes a thorough survey as an illustrative case study on distributions and top sites of MHK energy within the Might-Atlantic-Bight (MAB) with emphasis on the New Jersey (NJ) coastlines. In view of the needs in actual development of tidal power generation and sensitivity of tidal power to flow speed, the former being proportional to the third power of the latter, a high-resolution and detailed modeling is desired. Data with best available accuracy for coastlines, bathymetry, tributaries, etc. are used, meshes as fine as 20 m and less for the whole NJ coast are generated, and the unstructured grid finite volume coastal ocean model (FVCOM) and high performance computing (HPC) facilities are employed. Besides comparison with observation data, a series of numerical tests have been made to ensure reliability of the modeling results. A detailed tidal energy distribution and a list of top sites for tidal power are presented. It is shown that indeed sea-level-rise (SLR) affects the tidal energy distribution significantly. With SLR of 0.5 m and 1 m, tidal energy in NJ coastal waters increases by 21% and 43%, respectively, and the number of the top sties tends to decrease along the barrier islands facing the Atlantic Ocean and increase in the Delaware Bay and the Delaware River. On the basis of these results, further discussions are made on future development for accurate assessment of tidal energy.

Informatics Infrastructure for the Australian Neuroscience Community: The Multi-modal Australian ScienceS Imaging and Visualisation Environment and the Characterisation Virtual Laboratory

Informatics Infrastructure for the Australian Neuroscience Community: The Multi-modal Australian ScienceS Imaging and Visualisation Environment and the Characterisation Virtual Laboratory

MASSIVE: Applications in Neuroscience

MASSIVE: Applications in Neuroscience

Supporting HPC Analytics Applications with Access Patterns Using Data Restructuring and Data-Centric Scheduling Techniques in MapReduce

Current High Performance Computing (HPC) applications have seen an explosive growth in the size of data in recent years. Many application scientists have initiated efforts to integrate data-intensive computing into computational-intensive HPC facilities, particularly for data analytics. We have observed several scientific applications which must migrate their data from an HPC storage system to a data-intensive one for analytics. There is a gap between the data semantics of HPC storage and data-intensive system, hence, once migrated, the data must be further refined and reorganized. This reorganization must be performed before existing data-intensive tools such as MapReduce can be used to analyze data. This reorganization requires at least two complete scans through the data set and then at least one MapReduce program to prepare the data before analyzing it. Running multiple MapReduce phases causes significant overhead for the application, in the form of excessive I/O operations. That is for every MapReduce phase, a distributed read and write operation on the file system must be performed. Our contribution is to develop a MapReduce-based framework for HPC analytics to eliminate the multiple scans and also reduce the number of data preprocessing MapReduce programs. We also implement a data-centric scheduler to further improve the performance of HPC analytics MapReduce programs by maintaining the data locality. We have added additional expressiveness to the MapReduce language to allow application scientists to specify the logical semantics of their data such that 1) the data can be analyzed without running multiple data preprocessing MapReduce programs, and 2) the data can be simultaneously reorganized as it is migrated to the data-intensive file system. Using our augmented Map-Reduce system, MapReduce with Access Patterns (MRAP), we have demonstrated up to 33 percent throughput improvement in one real application, and up to 70 percent in an I/O kernel of another application. Our results for scheduling show up to 49 percent improvement for an I/O kernel of a prevalent HPC analysis application.

Computational Fluid Dynamics in Solid Earth Sciences–a HPC challenge

Presently, the Solid Earth Sciences started to move towards implementing High Performance Computational (HPC) research facilities. One of the key tenants of HPC is performance, which strongly depends on the interaction between software and hardware. In this paper, they are presented benchmark results from two HPC systems. Testing a Computational Fluid Dynamics (CFD) code specific for Solid Earth Sciences, the HPC system Horus, based on Gigabit Ethernet, performed reasonably well compared with its counterpart CyberDyn, based on Infiniband QDR fabric. However, the HPCC CyberDyn based on low-latency high-speed QDR network dedicated to MPI traffic outperformed the HPCC Horus. Due to the high-resolution simulations involved in geodynamic research studies, HPC facilities used in Earth Sciences should benefit from larger up-front investment in future systems that are based on high-speed interconnects.

A simulator to assess energy saving strategies and policies in HPC workloads

In recent years power consumption of high performance computing (HPC) clusters has become a growing problem due, e.g., to the economic cost of electricity, the emission of carbon dioxide (with negative impact on the environment), and the generation of heat (which reduces hardware reliability). In past work, we developed EnergySaving cluster, a software package that regulates the number of active nodes in an HPC facility to match the users' demands. In this paper, we extend this work by presenting a simulator for this tool that allows the evaluation and analysis of the benefits of applying different energy-saving strategies and policies, under realistic workloads, to different cluster configurations.

Strategies for MCR image analysis of large hyperspectral data-sets.

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data ‘binning’). Copyright © 2012 John Wiley & Sons, Ltd.

The “Chimera”: An Off-The-Shelf CPU/GPGPU/FPGA Hybrid Computing Platform

The nature of modern astronomy means that a number of interesting problems exhibit a substantial computational bound and this situation is gradually worsening. Scientists, increasingly fighting for valuable resources on conventional high-performance computing (HPC) facilities—often with a limited customizable user environment—are increasingly looking to hardware acceleration solutions. We describe here a heterogeneous CPU/GPGPU/FPGA desktop computing system (the “Chimera”), built with commercial-off-the-shelf components. We show that this platform may be a viable alternative solution to many common computationally bound problems found in astronomy, however, not without significant challenges. The most significant bottleneck in pipelines involving real data is most likely to be the interconnect (in this case the PCI Express bus residing on the CPU motherboard). Finally, we speculate on the merits of our Chimera system on the entire landscape of parallel computing, through the analysis of representative problems from UC Berkeley’s “Thirteen Dwarves.”

Automated Prediction of Protein Association Rate Constants

The association rate constants (k(a)) of proteins with other proteins or other macromolecular targets are a fundamental biophysical property. Observed rate constants span over ten orders of magnitude, from 1 to 10(10) M(-1)s(-1). Protein association can be rate limited either by the diffusional approach of the subunits to form a transient complex, with near-native separation and orientation but without short-range native interactions, or by the subsequent conformational rearrangement to form the native complex. Our transient-complex theory showed promise in predicting k(a) in the diffusion-limited regime. Here, we develop it into a web server called TransComp (http://pipe.sc.fsu.edu/transcomp/) and report on the server's accuracy and robustness based on applications to over 100 protein complexes. We expect this server to be a valuable tool for systems biology applications and for kinetic characterization of protein-protein and protein-nucleic acid association in general.

Virtualizing high performance computing

While virtualization is widely used in commercial enterprise environments, it has not to date played any significant role in High Performance Computing (HPC). However, with the rise of cloud computing and its promise of computing on demand, the HPC community's interest in virtualization (a key cloud enabler) is increasing. Beyond cloud computing, virtualization offers additional potential benefits for HPC, among them reactive and proactive application fault tolerance, secure and fault-isolated use of shared-resource clusters, dynamic provisioning, job migration, and support for heterogeneous HPC facilities. This paper describes both the promises and challenges in this new, emerging area, including a discussion of performance-related issues

Money for Research, Not Energy Bills: Finding Energy and Cost Savings in High-Performance Computer Facility Designs

High-performance computing facilities in the US consume enormous amounts of electricity,, cutting into research budgets and challenging efforts to reduce energy consumption and meet environmental goals. Facility designs that target efficiency greatly reduce energy demand. This case study describes strategies and technologies to achieve facility energy reductions through thoughtful design.

The Sicilian Grid Infrastructure for High Performance Computing

The conjugation of High Performance Computing (HPC) and Grid paradigm with applications based on commercial software is one among the major challenges of today e-Infrastructures. Several research communities from either industry or academia need to run high parallel applications based on licensed software over hundreds of CPU cores; a satisfactory fulfillment of such requests is one of the keys for the penetration of this computing paradigm into the industry world and sustainability of Grid infrastructures. This problem has been tackled in the context of the PI2S2 project that created a regional e-Infrastructure in Sicily, the first in Italy over a regional area. Present article will describe the features added in order to integrate an HPC facility into the PI2S2 Grid infrastructure, the adoption of the InifiniBand low-latency net connection, the gLite middleware extended to support MPI/MPI2 jobs, the newly developed license server and the specific scheduling policy adopted. Moreover, it will show the results of some relevant use cases belonging to Computer Fluid-Dynamics (Fluent, OpenFOAM), Chemistry (GAMESS), Astro-Physics (Flash) and Bio-Informatics (ClustalW)).

SPH simulation of free surface flow over a sharp-crested weir

In this paper the numerical simulation of a free surface flow over a sharp-crested weir is presented. Since in this case the usual shallow water assumptions are not satisfied, we propose to solve the problem using the full weakly compressible Navier–Stokes equations with the Tait equation of state for water. The numerical method used consists of the new meshless Smooth Particle Hydrodynamics (SPH) formulation proposed by Ferrari et al. (2009) [8], that accurately tracks the free surface profile and provides monotone pressure fields. Thus, the unsteady evolution of the complex moving material interface (free surface) can been properly solved. The simulations involving about half a million of fluid particles have been run in parallel on two of the most powerful High Performance Computing (HPC) facilities in Europe. The validation of the results has been carried out analysing the pressure field and comparing the free surface profiles obtained with the SPH scheme with experimental measurements available in literature [18]. A very good quantitative agreement has been obtained.

The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

Redirecting under‐utilised computer laboratories into cluster computing facilities

PurposeTo provide administrators at an Australian university with data on the feasibility of redirecting under‐utilised computer laboratories facilities into a distributed high performance computing facility.Design/methodology/approachThe individual log‐in records for each computer located in the computer laboratories at the university were investigated. The log‐in data were investigated over a 24‐hour/seven day a week period between June 2001 and August 2003. The data were analysed in terms of student access to the computer facilities during “normal” business hours, weekend times, and the semester breaks.FindingsThe computer laboratories were hugely under‐utilised, with less than 10 per cent of all log‐ins occurring during off peak times (7 pm‐8 am). Similarly, only weekends were likewise under‐utilised. This strongly suggests that this spare computer capacity could be used for alternate means during these times.Research limitations/implicationsFuture research needs to determine whether the needs of the general computer laboratory user who requires a stable and secure system can coexist with the users of a high performance computer facility where different software and differently configured computer systems are required.Practical implicationsThis research has the potential for universities to utilise more effectively their computer laboratory resources by allocating under‐utilised resources into other projects, such as to a high performance computing facility (HPCF). The cost of these re‐allocated resources would be a fraction of the cost compared to a scenario in which a separate dedicated HPCF had to be provided.Originality/valueThis paper suggests an alternate utilisation of the spare computing laboratory resources available at many universities.

UNICORE: uniform access to supercomputing as an element of electronic commerce

The battle for the desktop has been won by workstations and PCs. Offering computational capacity adequate for most applications, and superior user interfaces, they also incorporate the user’s link to a global information base via the World Wide Web. By contrast, High Performance Computing facilities tend to be increasingly isolated by such deterrents as geographical remoteness, architectural individuality, and the non-uniform operational policies of autonomous centres. The future of such centralised Supercomputing facilities and large scale data resources may depend to a large extent on the development of interfaces for accessing their resources from the user’s desktop in a uniform and user-friendly manner; otherwise, High Performance Computing may fall short of its full potential, becoming increasingly specialised and less competitive. In the most pessimistic scenario, the volume of the HPC market could fall below the threshold required for its economic survival in the free marketplace. The Uniform Interface to Computing Resources (UNICORE) project addresses these issues using the mechanisms of the World Wide Web (WWW).

Limitations on adiabatic normal modes in range-varying environments

Curvilinear coordinates are used to extend adiabatic normal modes to weak range-dependent environments including those with sloping bottoms. Reciprocal vertical wave numbers of a reference mode provide the coordinate scale factors. This approach is valid for negligible horizontal derivatives of intermodal vertical-wave number ratios. Large gradients in the bottom impedance make these ratios large, implying significant mode coupling in oceanic regions spanning both soft and hard terrains. Additionally, a large number of eigenvalues are needed to compute adiabatic normal-mode solutions for high-resolution acoustic fields. The direct solution of eigenvalue problems on a fine grid is often prohibitive. Alternatively, the eigenvalues may be interpolated to the fine grid. This approach usually requires extrapolation toward edges across which the horizontal wave number becomes imaginary at mode cutoff. One choice for an interpolation function is the integrated reciprocal vertical wave number. This function, proportional to water depth, is smooth and real throughout the cutoff region, while causing the horizontal wave number to vanish along the cutoff line. [Work supported by the Office of Naval Research and partially by DOD High Performance Computing facilities at NRL.]

Failure of Linear-Response-Theory for NaK Alloys**The project supported by the University of Texas High Performance Computing Facility, the Welch Foundation (Houston, TX) and the National Science Foundation under Grant No. DMR 9313645

As we previously did for Na, we calculate the Gibbs free energy of liquid and solid using linear-response-theory and molecular dynamics to obtain its melting temperature. The agreement with experiment is even better than that obtained for Na. We then attempted to determine the formation enthalpy of liquid and solid NaK alloys without success and discuss possible reasons for the failure of the method to yield agreement with experiment.

The automated interactive microscope (AIM) for investigating the functional dynamics of living cells: Status and vision

The current status and future development plans for the Automated Interactive Microscope (AIM), to better define the mechanisms of the function of living cells, is described. The development of AIM is fueled by biologists need to spatially and temporally correlate biochemical, molecular and genetic patterns to study cell functions such as division, locomotion and endocytosis. AIM will allow the investigator to use the cell as a “living microcuvette”.AIM redefines the meaning of the term “microscope” to include the functional capability of the microscope system provided by computerization, in addition to the more classical definition which emphasizes the opto-mechanical hardware. AIM is an next generation electronic light microscope imaging system which has grown out of our work in the development of the multimode light microscope. New functionality includes new experiment control facilities as well as related multidimensional image processing, image analysis and interactive data visualization. AIM is built around microscope hardware with high precision motion controls and a powerful host workstation computer linked, via a very high speed data gateway, with the high performance computing and communication (HPCC) facilities of the Pittsburgh Supercomputing Center (PSC).