Designing Computing System Architecture and Models for the HL-LHC era

This paper describes a programme to study the computing model in CMS after the next long shutdown near the end of the decade.Comment: Submitted to proceedings of the 21st International Conference on Computing in High Energy and Nuclear Physics (CHEP2015), Okinawa, Japa

Event Indexing Systems for Efficient Selection and Analysis of HERA Data

The design and implementation of two software systems introduced to improve the efficiency of offline analysis of event data taken with the ZEUS Detector at the HERA electron-proton collider at DESY are presented. Two different approaches were made, one using a set of event directories and the other using a tag database based on a commercial object-oriented database management system. These are described and compared. Both systems provide quick direct access to individual collision events in a sequential data store of several terabytes, and they both considerably improve the event analysis efficiency. In particular the tag database provides a very flexible selection mechanism and can dramatically reduce the computing time needed to extract small subsamples from the total event sample. Gains as large as a factor 20 have been obtained.Comment: Accepted for publication in Computer Physics Communication

Determination of the longitudinal structure function FLF_{L} at HERA

Recent results from the HERA experiment H1 on the longitudinal stucture function $F_{L}$ of the proton are presented. They include proton structure function analyses with particular emphasis on those kinematic regions which are sensitive to $F_{L}$. All results can be consistently described within the framework of perturbative QCD.Comment: 16 pages, 11 figures (requires iopart, iopams and epsfig); Talk presented in the Intern. Workshop on New Trends in HERA Physics 2001, 17-22 June 2001, Ringberg Castle, Tegernsee, Germany; To appear in the Proceeding

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems)

Computing plays an essential role in all aspects of high energy physics. As computational technology evolves rapidly in new directions, and data throughput and volume continue to follow a steep trend-line, it is important for the HEP community to develop an effective response to a series of expected challenges. In order to help shape the desired response, the HEP Forum for Computational Excellence (HEP-FCE) initiated a roadmap planning activity with two key overlapping drivers -- 1) software effectiveness, and 2) infrastructure and expertise advancement. The HEP-FCE formed three working groups, 1) Applications Software, 2) Software Libraries and Tools, and 3) Systems (including systems software), to provide an overview of the current status of HEP computing and to present findings and opportunities for the desired HEP computational roadmap. The final versions of the reports are combined in this document, and are presented along with introductory material.Comment: 72 page

The Longitudinal Structure Function at the Third Order

We compute the complete third-order contributions to the coefficient functions for the longitudinal structure function F_L, thus completing the next-to-next-to-leading order (NNLO) description of unpolarized electromagnetic deep-inelastic scattering in massless perturbative QCD. Our exact results agree with determinations of low even-integer Mellin moments and of the leading small-x terms in the flavour-singlet sector. In this letter we present compact and accurate parametrizations of the results and illustrate the numerical impact of the NNLO corrections.Comment: 11 pages, LaTeX, 4 eps-figures. DESY preprint number correcte

Beam Test of Silicon Strip Sensors for the ZEUS Micro Vertex Detector

For the HERA upgrade, the ZEUS experiment has designed and installed a high precision Micro Vertex Detector (MVD) using single sided micro-strip sensors with capacitive charge division. The sensors have a readout pitch of 120 microns, with five intermediate strips (20 micron strip pitch). An extensive test program has been carried out at the DESY-II testbeam facility. In this paper we describe the setup developed to test the ZEUS MVD sensors and the results obtained on both irradiated and non-irradiated single sided micro-strip detectors with rectangular and trapezoidal geometries. The performances of the sensors coupled to the readout electronics (HELIX chip, version 2.2) have been studied in detail, achieving a good description by a Monte Carlo simulation. Measurements of the position resolution as a function of the angle of incidence are presented, focusing in particular on the comparison between standard and newly developed reconstruction algorithms.Comment: 41 pages, 21 figures, 2 tables, accepted for publication in NIM

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing nterest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized both local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. In addition, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.Comment: 15 pages, 9 figure