Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imagingPostprint (author's final draft

A cross-layer approach to enhance QoS for multimedia applications over satellite

The need for on-demand QoS support for communications over satellite is of primary importance for distributed multimedia applications. This is particularly true for the return link which is often a bottleneck due to the large set of end-users accessing a very limited uplink resource. Facing this need, Demand Assignment Multiple Access (DAMA) is a classical technique that allows satellite operators to offer various types of services, while managing the resources of the satellite system efficiently. Tackling the quality degradation and delay accumulation issues that can result from the use of these techniques, this paper proposes an instantiation of the Application Layer Framing (ALF) approach, using a cross-layer interpreter(xQoS-Interpreter). The information provided by this interpreter is used to manage the resource provided to a terminal by the satellite system in order to improve the quality of multimedia presentations from the end users point of view. Several experiments are carried out for different loads on the return link. Their impact on QoS is measured through different application as well as network level metrics

Composing Systemic Aspects into Component-Oriented DOC Middleware

The advent and maturation of component-based middleware frameworks have sim-plified the development of large-scale distributed applications by separating system devel-opment and configuration concerns into different aspects that can be specified and com-posed at various stages of the application development lifecycle. Conventional component middleware technologies, such as J2EE [73] and .NET [34], were designed to meet the quality of service (QoS) requirements of enterprise applications, which focus largely on scalability and reliability. Therefore, conventional component middleware specifications and implementations are not well suited for distributed real-time and embedded (DRE) ap-plications with more stringent QoS requirements, such as low latency/jitter, timeliness, and online fault recovery. In the DRE system development community, a new generation of enhanced commercial off-the-shelf (COTS) middleware, such as Real-time CORBA 1.0 (RT-CORBA)[39], is increasingly gaining acceptance as (1) the cost and time required to develop and verify DRE applications precludes developers from implementing complex DRE applications from scratch and (2) implementations of standard COTS middleware specifications mature and encompass key QoS properties needed by DRE systems. However, although COTS middleware standardizes mechanisms to configure and control underlying OS support for an application’s QoS requirements, it does not yet provide sufficient abstractions to separate QoS policy configurations such as real-time performance requirements, from application functionality. Developers are therefore forced to configure QoS policies in an ad hoc way, and the code to configure these policies is often scattered throughout and tangled with other parts of a DRE system. As a result, it is hard for developers to configure, validate, modify, and evolve complex DRE systems consistently. It is therefore necessary to create a new generation of QoS-enabled component middleware that provides more comprehensive support for addressing QoS-related concerns modularly, so that they can be introduced and configured as separate systemic aspects. By analyzing and identifying the limitations of applying conventional middleware technologies for DRE applications, this dissertation presents a new design and its associated techniques for enhancing conventional component-oriented middleware to provide programmability of DRE relevant real-time QoS concerns. This design is realized in an implementation of the standard CORBA Component Model (CCM) [38], called the Component-Integrated ACE ORB (CIAO). This dissertation also presents both architectural analysis and empirical results that demonstrate the effectiveness of this approach. This dissertation provides three contributions to the state of the art in composing systemic behaviors into component middleware frameworks. First, it illustrates how component middleware can simplify development and evolution of DRE applications while ensuring stringent QoS requirements by composing systemic QoS aspects. Second, it contributes to the design and implementation of QoS-enabled CCM by analyzing and documenting how systemic behaviors can be composed into component middleware. Finally, it presents empirical and analytical results to demonstrate the effectiveness and the advantage of composing systemic behaviors in component middleware. The work in this dissertation has a broader impact beyond the CCM in which it was developed, as it can be applied to other component-base middleware technologies which wish to support DRE applications

Coscheduling techniques and monitoring tools for non-dedicated cluster computing

Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system when a parallel job is executed jointly with local workloads, balancing parallel perfor-mance against the local interactive response. Explicit and implicit coscheduling techniques in a PVM-Linux NOW (or cluster) have been implemented. Furthermore, dynamic coscheduling remains an open question when parallel jobs are executed in a non-dedicated Cluster. A basis model for dynamic coscheduling in Cluster systems is presented in this paper. Also, one dynamic coscheduling algorithm for this model is proposed. The applicability of this algorithm has been proved and its performance ana-lyzed by simulation. Finally, a new tool (named Monito) for monitoring the different queues of messages in such an environments is presented. The main aim of implementing this facility is to provide a mean of capturing the bottlenecks and overheads of the communication system in a PVM-Linux cluster.Facultad de Informátic

Secure FaaS orchestration in the fog: how far are we?

AbstractFunction-as-a-Service (FaaS) allows developers to define, orchestrate and run modular event-based pieces of code on virtualised resources, without the burden of managing the underlying infrastructure nor the life-cycle of such pieces of code. Indeed, FaaS providers offer resource auto-provisioning, auto-scaling and pay-per-use billing at no costs for idle time. This makes it easy to scale running code and it represents an effective and increasingly adopted way to deliver software. This article aims at offering an overview of the existing literature in the field of next-gen FaaS from three different perspectives: (i) the definition of FaaS orchestrations, (ii) the execution of FaaS orchestrations in Fog computing environments, and (iii) the security of FaaS orchestrations. Our analysis identify trends and gaps in the literature, paving the way to further research on securing FaaS orchestrations in Fog computing landscapes