Rafał Kluszczyński

Processing the biomedical data on the grid using the UNICORE workflow system

The huge amount of the biological and biomedical data increases demand for significant disk space and computer power to store and process them. From its beginning the Grid has been considered as possibility to provide such resources for the life sciences community. In this paper authors focus on the UNICORE system which enables scientists to access Grid resources in a seamless and secure way. Authors have used the UNICORE middleware to automate experimental and computational procedure to determine the spectrum of mutations in mitochondrial genomes of normal and colorectal cancer cells. The computational and storage resources have been provided by Polish National Grid Infrastructure PL-Grid.

Reservations for Compute Resources in Federated e-Infrastructure

This paper presents work done to prepare compute resource reservations in the PL-Grid Infrastructure. A compute resource reservation allows a user to allocate some fraction of resources for exclusive access, when reservation is prepared. That way the user is able to run his/her job without waiting for allocating resources in a batch system. In the PL-Grid Infrastructure reservations can be allocated up to amount negotiated in a PL-Grid grant. One way of getting reservation is allocation by a resource administrator. Another way is to use predefined pool of resources accessible by various middleware. In both approaches once obtained, reservations identifiers can be used by middleware during job submissions. Enabling reservations requires changes in middleware. The modifications needed in each middleware will be described. The possible extension of existing reservation model in the PL-Grid Infrastructure can be envisaged: reservation usage normalization and reservation accounting. The reservations are created and utilized in the users context, so there must be a way to pass the reservation details from the user-level tools to a batch system. Each of PL-Grid supported middleware, namely gLite, UNICORE and QosCosGrid, required adaptations to implement this goal.

Integrating Slurm Batch System with European and Polish Grid Infrastructures

ICM, one of the major Polish HPC resource providers, migrated to the Slurm batch system as the first site in the PL-Grid and WLCG grid infrastructures. This article describes the Slurm integration issues and the solutions developed. The integration was focused on several areas where grid middleware interacts with the batch scheduling system, additionally taking into consideration the PL-Grid specifics. In particular, the resource usage accounting required a dedicated Slurm support and the scientific grants enforcement policy needed a new implementation. What is more, in this work we present the reasons of the Slurm adoption and other improvements that were necessary to handle the increasing load of the grid site.

Development of Domain-Specific Solutions Within the Polish Infrastructure for Advanced Scientific Research

The Polish Grid computing infrastructure was established during the PL-Grid project (2009–2012). The main purpose of this Project was to provide the Polish scientists with an IT basic platform, allowing them to conduct interdisciplinary research on a national scale, and giving them transparent access to international grid resources via international grid infrastructures. Currently, the infrastructure is maintained and extended within a follow-up PLGrid Plus project (2011–2014). Its main objective is to increase the potential of the Polish Science by providing necessary IT services for research teams in Poland, in line with European solutions. The paper presents several examples of the domain-specific computational environments, developed within the Project. For particular environments, specialized IT solutions are prepared, i.e. dedicated software implementation and infrastructure adaptation, suited for particular researchers groups’ demands.

Grid services for genomic research. Polish national grid perspective

In this paper we present grid services for the biomolecular community offered by the Polish National Grid (Polish NGI). This work is motivated by the fact that in many application areas including life sciences there is increasing demand for disk space and computer power to store and process data. Emerging technologies such as Next Generation Sequencing (NGS) put additional stress on this demand. The amount of data which biologists have to handle is usually too big to be stored and processed in the laboratory using desktop or even more powerful single computers. The ultimate solution is grid technology offering seamless access to the distributed storage and computational resources. There has been number of different grid infrastructures used. The solution built using UNICORE middleware is example of the most successful one. In this paper we present the UNICORE installation in the Polish NGI. We provide details of the middleware deployment on the PL-Grid infrastructure. Overview of the bioinformatics related services is extended by the details of the grid deployment of the widely used bioinformatic applications such as BLAST. We also provide description of the grid infrastructure and services developed to support gene sequencing and its use in the diagnostics process. The storage and computational grid services are fully integrated with the sequencing equipment to make whole process seamless and easy to use. The described solution allowed to simplify analysis of sequencing results and make them available in the short time feasible for medical diagnosis.

Parallel version of image segmentation algorithm using polygonal markov fields

In this paper we present an application of parallel simulated annealing method to a segmentation algorithm using polygonal Markov fields. After a brief presentation of the algorithm and a general scheme of parallelization methods using simulated annealing technique, there is presented parallel approach to the segmentation algorithm with different synchronization scenarios. Authors also present results of the parallelization of the segmentation algorithm. There is discussed comparison between simulations with different synchronization scenarios applied to the multiple-trial approach of simulated annealing technique. Some simulations based on the number of threads are presented as well.