Realtime processing of LOFAR data for the detection of nano-second pulses from the Moon

The low flux of the ultra-high energy cosmic rays (UHECR) at the highest energies provides a challenge to answer the long standing question about their origin and nature. Even lower fluxes of neutrinos with energies above $10^{22}$ eV are predicted in certain Grand-Unifying-Theories (GUTs) and e.g.\ models for super-heavy dark matter (SHDM). The significant increase in detector volume required to detect these particles can be achieved by searching for the nano-second radio pulses that are emitted when a particle interacts in Earth's moon with current and future radio telescopes. In this contribution we present the design of an online analysis and trigger pipeline for the detection of nano-second pulses with the LOFAR radio telescope. The most important steps of the processing pipeline are digital focusing of the antennas towards the Moon, correction of the signal for ionospheric dispersion, and synthesis of the time-domain signal from the polyphased-filtered signal in frequency domain. The implementation of the pipeline on a GPU/CPU cluster will be discussed together with the computing performance of the prototype.Comment: Proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP2016), US

HyperTransport Over Ethernet - A Scalable, Commodity Standard for Resource Sharing in the Data Center

Future data center configurations are driven by total cost of ownership (TCO) for specific performance capabilities. Low-latency interconnects are central to performance, while the use of commodity interconnects is central to cost. This paper reports on an effort to combine a very high-performance, commodity interconnect (HyperTransport) with a high-volume interconnect (Ethernet). Previous approaches to extending Hyper-Transport (HT) over a cluster used custom FPGA cards [5] and proprietary extensions to coherence schemes [22], but these solutions mainly have been adopted for use in research-oriented clusters. The new HyperShare strategy from the HyperTransport Consortium proposes several new ways to create low-cost, commodity clusters that can support scalable high performance computing in either clusters or in the data center. HyperTransport over Ethernet (HToE) is the newest specification in the HyperShare strategy that aims to combine favorable market trends with a highbandwidth and low-latency hardware solution for noncoherent sharing of resources in a cluster. This paper illustrates the motivation behind using 10, 40, or 100 Gigabit Ethernet as an encapsulation layer for Hyper-Transport, the requirements for the HToE specification, and engineering solutions for implementing key portions of the specification

Cross-level Validation of Topological Quantum Circuits

Quantum computing promises a new approach to solving difficult computational problems, and the quest of building a quantum computer has started. While the first attempts on construction were succesful, scalability has never been achieved, due to the inherent fragile nature of the quantum bits (qubits). From the multitude of approaches to achieve scalability topological quantum computing (TQC) is the most promising one, by being based on an flexible approach to error-correction and making use of the straightforward measurement-based computing technique. TQC circuits are defined within a large, uniform, 3-dimensional lattice of physical qubits produced by the hardware and the physical volume of this lattice directly relates to the resources required for computation. Circuit optimization may result in non-intuitive mismatches between circuit specification and implementation. In this paper we introduce the first method for cross-level validation of TQC circuits. The specification of the circuit is expressed based on the stabilizer formalism, and the stabilizer table is checked by mapping the topology on the physical qubit level, followed by quantum circuit simulation. Simulation results show that cross-level validation of error-corrected circuits is feasible.Comment: 12 Pages, 5 Figures. Comments Welcome. RC2014, Springer Lecture Notes on Computer Science (LNCS) 8507, pp. 189-200. Springer International Publishing, Switzerland (2014), Y. Shigeru and M.Shin-ichi (Eds.

Cluster Evaluation of Density Based Subspace Clustering

Clustering real world data often faced with curse of dimensionality, where real world data often consist of many dimensions. Multidimensional data clustering evaluation can be done through a density-based approach. Density approaches based on the paradigm introduced by DBSCAN clustering. In this approach, density of each object neighbours with MinPoints will be calculated. Cluster change will occur in accordance with changes in density of each object neighbours. The neighbours of each object typically determined using a distance function, for example the Euclidean distance. In this paper SUBCLU, FIRES and INSCY methods will be applied to clustering 6x1595 dimension synthetic datasets. IO Entropy, F1 Measure, coverage, accurate and time consumption used as evaluation performance parameters. Evaluation results showed SUBCLU method requires considerable time to process subspace clustering; however, its value coverage is better. Meanwhile INSCY method is better for accuracy comparing with two other methods, although consequence time calculation was longer.Comment: 6 pages, 15 figure

Efficient Resource Matching in Heterogeneous Grid Using Resource Vector

In this paper, a method for efficient scheduling to obtain optimum job throughput in a distributed campus grid environment is presented; Traditional job schedulers determine job scheduling using user and job resource attributes. User attributes are related to current usage, historical usage, user priority and project access. Job resource attributes mainly comprise of soft requirements (compilers, libraries) and hard requirements like memory, storage and interconnect. A job scheduler dispatches jobs to a resource if a job's hard and soft requirements are met by a resource. In current scenario during execution of a job, if a resource becomes unavailable, schedulers are presented with limited options, namely re-queuing job or migrating job to a different resource. Both options are expensive in terms of data and compute time. These situations can be avoided, if the often ignored factor, availability time of a resource in a grid environment is considered. We propose resource rank approach, in which jobs are dispatched to a resource which has the highest rank among all resources that match the job's requirement. The results show that our approach can increase throughput of many serial / monolithic jobs.Comment: 10 page