CERN openlab Whitepaper on Future IT Challenges in Scientific Research

This whitepaper describes the major IT challenges in scientific research at CERN and several other European and international research laboratories and projects. Each challenge is exemplified through a set of concrete use cases drawn from the requirements of large-scale scientific programs. The paper is based on contributions from many researchers and IT experts of the participating laboratories and also input from the existing CERN openlab industrial sponsors. The views expressed in this document are those of the individual contributors and do not necessarily reflect the view of their organisations and/or affiliates

Cloud Computing and Quality of Service: Issues and Developments

Cloud computing is a dynamic information technology (IT) paradigm that delivers on demand computing resources to a user over a network infrastructure. The Cloud Service Provider (CSP) offers applications which can be accessed online to users. Such applications can be shared by more than one user. CSPs provides programming interfaces that allows customers to build and deploy applications on the cloud; as well as providing massive storage and computing infrastructure to users. Users usually have no control on how data is stored on the cloud or where the underlying resources are located. With this limited control, customers’ requirements and Quality of Service (QoS) expectations from CSPs are spelt out using a Service Level Agreement (SLA). It is thus imperative to have the adequate QoS guarantees from a CSP. This paper examines trends in the area of Cloud computing QoS and provides a guide for future research. A review and survey of existing works in literature is done in order to identify these Cloud QoS trends. The finding is that the ultimate expectation of any QoS metrics or model is the related to cost concern for both the CSP and user

RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene

The State-of-the-Art of Set Visualization

Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net