Gábor Gombás

Programming scientific and distributed workflow with Triana services

In this paper, we discuss a real‐world application scenario that uses three distinct types of workflow within the Triana problem‐solving environment: serial scientific workflow for the data processing of gravitational wave signals; job submission workflows that execute Triana services on a testbed; and monitoring workflows that examine and modify the behaviour of the executing application. We briefly describe the Triana distribution mechanisms and the underlying architectures that we can support. Our middleware independent abstraction layer, called the Grid Application Prototype (GAP), enables us to advertise, discover and communicate with Web and peer‐to‐peer (P2P) services. We show how gravitational wave search algorithms have been implemented to distribute both the search computation and data across the European GridLab testbed, using a combination of Web services, Globus interaction and P2P infrastructures. Copyright

P-GRADE: a grid programming environment

P-GRADE provides a high-level graphical environment to develop parallel applications transparently both for parallel systems and the Grid. P-GRADE supports the interactive execution of parallel programs as well as the creation of a Condor, Condor-G or Globus job to execute parallel programs in the Grid. In P-GRADE, the user can generate either PVM or MPI code according to the underlying Grid where the parallel application should be executed. PVM applications generated by P-GRADE can migrate between different Grid sites and as a result P-GRADE guarantees reliable, fault-tolerant parallel program execution in the Grid. The GRM/PROVE performance monitoring and visualisation toolset has been extended towards the Grid and connected to a general Grid monitor (Mercury) developed in the EU GridLab project. Using the Mercury/GRM/PROVE Grid application monitoring infrastructure any parallel application launched by P-GRADE can be remotely monitored and analysed at run time even if the application migrates among Grid sites. P-GRADE supports workflow definition and co-ordinated multi-job execution for the Grid. Such workflow management can provide parallel execution at both inter-job and intra-job level. Automatic checkpoint mechanism for parallel programs supports the migration of parallel jobs inside the workflow providing a fault-tolerant workflow execution mechanism. The paper describes all of these features of P-GRADE and their implementation concepts.

EDGeS: Bridging EGEE to BOINC and XtremWeb

Desktop Grids, such as XtremWeb and BOINC, and Service Grids, such as EGEE, are two different approaches for science communities to gather computing power from a large number of computing resources. Nevertheless, little work has been done to combine these two Grid technologies in order to establish a seamless and vast Grid resource pool. In this paper we present the EGEE Service Grid, the BOINC and XtremWeb Desktop Grids. Then, we present the EDGeS solution to bridge the EGEE Service Grid with the BOINC and XtremWeb Desktop Grids.

Resource and Job Monitoring in the Grid

In a complex system like the grid monitoring is essential for understanding its operation, debugging, failure detection and for performance optimisation. In this paper a flexible monitoring architecture is introduced that provides advanced functions like actuators and guaranteed data delivery. The application of the monitoring system for grid job and resource monitoring, and the integration of the monitoring system with other grid services is also described.

SZTAKI Desktop Grid (SZDG): A Flexible and Scalable Desktop Grid System

SZTAKI Desktop Grid (SZDG) is an extension of BOINC in order to make it more flexible, versatile and scalable in terms of enabling the interconnection of different BOINC projects and execution of parameter sweep applications from a generic, high level user interface without the intervention of the BOINC project administrator. The paper describes the main concepts and features of SZDG. Among the many novel features the two most important will be described in detail. First, the paper describes those extensions that enable the easy development and execution of parameter sweep applications on SZDGs. The second part of the paper describes how SZDGs can be organized into a hierarchical interconnection scheme that enables to use SZDGs as building blocks to create higher level SZDGs.

SZTAKI Desktop Grid: a Modular and Scalable Way of Building Large Computing Grids

So far BOINC based desktop grid systems have been applied at the global computing level. This paper describes an extended version of BOINC called SZTAKI desktop grid (SZDG) that aims at using desktop grids (DGs) at local (enterprise/institution) level. The novelty of SZDG is that it enables the hierarchical organisation of local DGs, i.e., clients of a DG can be DGs at a lower level that can take work units from their higher level DG server. More than that, even clusters can be connected at the client level and hence work units can contain complete MPI programs to be run on the client clusters. In order to easily create master/worker type DG applications a new API, called as the DC-API has been developed. SZDG and DC-API has been successfully applied both at the global and local level, both in academic institutions and in companies to solve problems requiring large computing power.

Performance evaluation on grids: directions, issues, and open problems

Grids are semantically different from other distributed systems. Therefore, performance analysis, just like any other technique requires careful reconsideration. We analyse the fundamental differences between grids and other systems and point out the special requirements raised to performance analysis. The main aim is to survey the special problems, the possible directions and the existing solutions. A monitoring system, that is able to support the posed requirements is introduced as an example.

Sztaki Desktop Grid: Building a Scalable, Secure Platform for Desktop Grid Computing

In this paper we present a concept how separate desktop grids can be used as building blocks for larger scale grids by organizing them in a hierarchical tree. We describe an enhanced security model which satisfies the requirements of the hierarchical setup and is aimed for real-world deployment.

Interoperability of BOINC and EGEE

Today basically two types of grid systems are in use: service grids and desktop grids. Service grids offer an infrastructure for grid users, thus require notable management to keep the service running. On the other hand, desktop grids aim to utilize free CPU cycles of cheap desktop PCs, are easy to set up, but the availability towards users is limited compared to the service grid. The aim of the EDGeS project is to create an integrated infrastructure that combines the advantages of the two grid concepts. A building block of this infrastructure is bridging between the different grid types. In this paper, we first focus on bridging from BOINC-based desktop grids towards EGEE-like service grids, i.e., making desktop grids able to utilize free service grid resources. The solution is based on a generic grid to grid bridge, called as, 3G Bridge. In the second part of the paper we show how the 3G Bridge and EDGeS Bridge services can be used to realize the reverse direction interconnection of BOINC and EGEE grids, i.e., sending EGEE jobs in a user transparent way to BOINC systems that are connected to EGEE VOs. This is the first paper in which we publish the full two-directional bridging between BOINC and EGEE grids.

EDGeS: The common boundary between service and desktop grids

Service grids and desktop grids are both promoted by their supportive communities as great solutions for solving the available compute power problem and helping to balance loads across network systems. Little work, however, has been undertaken to blend these two technologies together. In this paper we introduce a new EU project, that is building technological bridges to facilitate service and desktop grid interoperability. We provide a taxonomy and background into service grids, such as EGEE and desktop grids or volunteer computing platforms, such as BOINC and XtremWeb. We then describe our approach for identifying translation technologies between service and desktop grids. The individual themes discuss the actual bridging technologies employed and the distributed data issues surrounding deployment.