Grid tool integration within the eMinerals Project

In this article we describe the eMinerals mini grid, which is now running in production mode. Thisis an integration of both compute and data components, the former build upon Condor, PBS and thefunctionality of Globus v2, and the latter being based on the combined use of the Storage ResourceBroker and the CCLRC data portal. We describe how we have integrated the middleware components,and the different facilities provided to the users for submitting jobs within such an environment. We willalso describe additional functionality we found it necessary to provide ourselves

Android on x86

Computer scienc

Cultural Issues in Software Estimation: From Intuition to Model Based Estimation in Upgrade Projects

This paper discusses issues related to change in culture that happens when software estimation becomes scientific, methodical and predictive. From a person based intuitive approach to model based estimation techniques, the approach necessitates a change in mindset and culture. This change in culture has been noticed in upgrade projects. Upgrades play an important role in product life cycle. A product is released with required features to meet immediate requirements of the customers. Any additional or modifications to features are carried through upgrade projects. These upgrades planned well in advance by the product developing organizations are made available to customers through published road map for the products. And hence it is important to be able to predict the effort required for these upgrade projects accurately and consistently. The objective of this research was to study cultural issues while developing an estimation model that would increase accuracy, predictability of estimation in upgrade projects. The methodology adopted in this research work was to use primary sources of data to develop an estimation model for upgrade projects and test this model in live upgrade projects. The results from the research showed that the level of accuracy for estimation increased, predictability in delivery was higher without comprising quality of final deliverables. The culture also went through a change through training and mentoring

Evaluation of low-power architectures in a scientific computing environment

HPC (High Performance Computing) represents, together with theory and experiments, the third pillar of science. Through HPC, scientists can simulate phenomena otherwise impossible to study. The need of performing larger and more accurate simulations requires to HPC to improve every day. HPC is constantly looking for new computational platforms that can improve cost and power efficiency. The Mont-Blanc project is a EU funded research project that targets to study new hardware and software solutions that can improve efficiency of HPC systems. The vision of the project is to leverage the fast growing market of mobile devices to develop the next generation supercomputers. In this work we contribute to the objectives of the Mont-Blanc project by evaluating performance of production scientific applications on innovative low power architectures. In order to do so, we describe our experiences porting and evaluating sate of the art scientific applications on the Mont-Blanc prototype, the first HPC system built with commodity low power embedded technology. We then extend our study to compare off-the-shelves ARMv8 platforms. We finally discuss the most impacting issues encountered during the development of the Mont-Blanc prototype system

Using Rust as a Complement to C for Embedded Systems Software Development

Rust aims to bring safety to low-level programming by using zero-cost ab- stractions. These provide, among other things, guaranteed memory safety and threading without data races. Garbage collected languages have become popular to guarantee safety, but in performance critical, memory limited or real time applications, it is not an ideal solution. Rust is safe and still has manual memory management, with strict rules. This report presents a case study of using the Rust language and associated tooling such as debuggers and IDEs in practise. The study was carried out by porting 5000+ lines of an embedded Linux daemon to Rust. Rust upholds the safety and zero-cost claims. Using Rust has been found to aid in achieving an improved, shorter, more expressive architecture. The learning curve is a bit steep, but productivity has been found to be high once learned. Tooling support is mature, but IDEs are not yet full featured.Programmeringsspråket Rust utvecklas av en grupp som anser att det saknas språk som passar lågnivåutveckling och samtidigt är säkra. Rust har utvärderats genom att översätta 5000+ rader C-kod i ett inbyggt system. Rust levererar säkerhet, är smidigt och är inte resursintensivt

Distributed computing and farm management with application to the search for heavy gauge bosons using the ATLAS experiment at the LHC (CERN)

The Standard Model of particle physics describes the strong, weak, and electromagnetic forces between the fundamental particles of ordinary matter. However, it presents several problems and some questions remain unanswered so it cannot be considered a complete theory of fundamental interactions. Many extensions have been proposed in order to address these problems. Some important recent extensions are the Extra Dimensions theories. In the context of some models with Extra Dimensions of size about $1 TeV^{-}1$, in particular in the ADD model with only fermions confined to a D-brane, heavy Kaluza-Klein excitations are expected, with the same properties as SM gauge bosons but more massive. In this work, three hadronic decay modes of some of such massive gauge bosons, Z* and W*, are investigated using the ATLAS experiment at the Large Hadron Collider (LHC), presently under construction at CERN. These hadronic modes are more difficult to detect than the leptonic ones, but they should allow a measurement of the couplings between heavy gauge bosons and quarks. The events were generated using the ATLAS fast simulation and reconstruction MC program Atlfast coupled to the Monte Carlo generator PYTHIA. We found that for an integrated luminosity of $3 × 10^{5} pb^{-}1$ and a heavy gauge boson mass of 2 TeV, the channels Z*->bb and Z*->tt would be difficult to detect because the signal would be very small compared with the expected backgrou nd, although the significance in the case of Z*->tt is larger. In the channel W*->tb , the decay might yield a signal separable from the background and a significance larger than 5 so we conclude that it would be possible to detect this particular mode at the LHC. The analysis was also performed for masses of 1 TeV and we conclude that the observability decreases with the mass. In particular, a significance higher than 5 may be achieved below approximately 1.4, 1.9 and 2.2 TeV for Z*->bb , Z*->tt and W*->tb respectively. The LHC will start to operate in 2008 and collect data in 2009. It will produce roughly 15 Petabytes of data per year. Access to this experimental data has to be provided for some 5,000 scientists working in 500 research institutes and universities. In addition, all data need to be available over the estimated 15-year lifetime of the LHC. The analysis of the data, including comparison with theoretical simulations, requires an enormous computing power. The computing challenges that scientists have to face are the huge amount of data, calculations to perform and collaborators. The Grid has been proposed as a solution for those challenges. The LHC Computing Grid project (LCG) is the Grid used by ATLAS and the other LHC experiments and it is analised in depth with the aim of studying the possible complementary use of it with another Grid project. That is the Berkeley Open Infrastructure for Network C omputing middle-ware (BOINC) developed for the SETI@home project, a Grid specialised in high CPU requirements and in using volunteer computing resources. Several important packages of physics software used by ATLAS and other LHC experiments have been successfully adapted/ported to be used with this platform with the aim of integrating them into the LHC@home project at CERN: Atlfast, PYTHIA, Geant4 and Garfield. The events used in our physics analysis with Atlfast were reproduced using BOINC obtaining exactly the same results. The LCG software, in particular SEAL, ROOT and the external software, was ported to the Solaris/sparc platform to study it's portability in general as well. A testbed was performed including a big number of heterogeneous hardware and software that involves a farm of 100 computers at CERN's computing center (lxboinc) together with 30 PCs from CIEMAT and 45 from schools from Extremadura (Spain). That required a preliminary study, development and creation of components of the Quattor software and configuration management tool to install and manage the lxboinc farm and it also involved the set up of a collaboration between the Spanish research centers and government and CERN. The testbed was successful and 26,597 Grid jobs were delivered, executed and received successfully. We conclude that BOINC and LCG are complementary and useful kinds of Grid that can be used by ATLAS and the other LHC experiments. LCG has very good data distribution, management and storage capabilities that BOINC does not have. In the other hand, BOINC does not need high bandwidth or Internet speed and it also can provide a huge and inexpensive amount of computing power coming from volunteers. In addition, it is possible to send jobs from LCG to BOINC and vice versa. So, possible complementary cases are to use volunteer BOINC nodes when the LCG nodes have too many jobs to do or to use BOINC for high CPU tasks like event generators or reconstructions while concentrating LCG for data analysis

Hardware Acceleration of Network Intrusion Detection System Using FPGA

This thesis presents new algorithms and hardware designs for Signature-based Network Intrusion Detection System (SB-NIDS) optimisation exploiting a hybrid hardwaresoftware co-designed embedded processing platform. The work describe concentrates on optimisation of a complete SB-NIDS Snort application software on a FPGA based hardware-software target rather than on the implementation of a single functional unit for hardware acceleration. Pattern Matching Hardware Accelerator (PMHA) based on Bloom filter was designed to optimise SB-NIDS performance for execution on a Xilinx MicroBlaze soft-core processor. The Bloom filter approach enables the potentially large number of network intrusion attack patterns to be efficiently represented and searched primarily using accesses to FPGA on-chip memory. The thesis demonstrates, the viability of hybrid hardware-software co-designed approach for SB-NIDS. Future work is required to investigate the effects of later generation FPGA technology and multi-core processors in order to clearly prove the benefits over conventional processor platforms for SB-NIDS. The strengths and weaknesses of the hardware accelerators and algorithms are analysed, and experimental results are examined to determine the effectiveness of the implementation. Experimental results confirm that the PMHA is capable of performing network packet analysis for gigabit rate network traffic. Experimental test results indicate that our SB-NIDS prototype implementation on relatively low clock rate embedded processing platform performance is approximately 1.7 times better than Snort executing on a general purpose processor on PC when comparing processor cycles rather than wall clock time