Concepció Roig

A New Task Graph Model for Mapping Message Passing Applications

The exploitation of parallelism in a message passing platform implies a previous modeling phase of the parallel application as a task graph, which properly reflects its temporal behavior. In this paper, we analyze the classical task graph models of the literature and their drawbacks when modeling message passing programs with an arbitrary task structure. We define a new task graph model called temporal task interaction graph (TTIG) that integrates the classical models used in the literature. The TTIG allows us to explicitly capture the ability of concurrency of adjacent tasks for applications where adjacent tasks can communicate at any point inside them. A mapping strategy is developed from this model, which minimizes the expected execution time by properly exploiting task parallelism. The effectiveness of this approach has been proved in different experimentation scopes for a wide range of message passing applications.

A secure elliptic curve-based RFID protocol

Nowadays, the use of Radio Frequency Identification (RFID) systems in industry and stores has increased. Nevertheless, some of these systems present privacy problems that may discourage potential users. Hence, high confidence and effient privacy protocols are urgently needed. Previous studies in the literature proposed schemes that are proven to be secure, but they have scalability problems. A feasible and scalable protocol to guarantee privacy is presented in this paper. The proposed protocol uses elliptic curve cryptography combined with a zero knowledge-based authentication scheme. An analysis to prove the system secure, and even forward secure is also provided.

A new model for static mapping of parallel applications with task and data parallelism

The efficient mapping of parallel tasks is essential in order to exploit the gain from parallelisation. In this work, we focus on modelling and mapping message-passing applications that are defined by the programmer with an arbitrary interaction pattern among tasks. A new model is proposed, known as TTIG (Temporal Task Interaction Graph), which captures not only computation and communication costs, but also the percentages of concurrency between tasks. From this model, a mapping strategy is developed that minimises expected execution time by properly exploiting task parallelism. The effectiveness of this approach has been proven for a real image-processing application on a cluster of PCs.

Modelling message-passing programs for static mapping

An efficient mapping of a parallel program in the processors is vital for achieving a high performance on a parallel computer. When the structure of the parallel program in terms of its task execution times, task dependencies, and amount communication data, is known a priori, mapping can be accomplished statically at compile time. Mapping algorithms start from a parallel application model and map automatically tasks to processors in order to minimise the execution time of the program. In this paper we discuss the current models used in mapping parallel programs: Task Precedence Graph (TPG), Task Interaction Graph (TIG) and we define a new model called Temporal Task Interaction Graph (TTIG). The contribution of the TTIG is that it enhances these two previous models with the ability to explicitly capture the potential degree of parallel execution between adjacent tasks allowing the development of efficient mapping algorithms. Experimentation had been performed in order to show the effectiveness of TTIG model for a set of graphs. The results are compared with the optimal assignment and the obtained using TIG model and they confirm that using the TTIG model, better assignments can be obtained.

Optimizing Latency under Throughput Requirements for Streaming Applications on Cluster Execution

Parallelism in applications that act on a stream of input data can be exploited with two different approaches, spatial and temporal. In this paper we propose a new task mapping algorithm, called EXPERT, to exploit temporal parallelism efficiently when the streaming application is running in a pipeline fashion. We compare the performance of spatial and temporal approaches, in terms of latency and throughput for a video compression application. The results show that the pipeline execution with the task assignment provided by EXPERT algorithm, significantly overcomes spatial parallelism. Additionally, this temporal parallelism presents better scalability results when the dimension of the problem is augmented

A Scalable Hybrid P2P System for MMOFPS

Nowadays, MMOGs are extensively used as they provide the ability for centralized gaming with many players. MMOGs can be classified into three different categories: MMRPOG that are role games, MMORTS based on real-time strategy games and MMOFPS named as first person shooter games. The computational requirements of these categories are different. In this paper we focus on MMOFPS, whose main gaming requirements are low latency values and scalability. We propose a new system called OnDeGaS (On Demand Game Service), that combines the functionalities of a centralized server infrastructure with a distributed P2P topology, in such a way that the system can grow at any moment according to the existing demand, by maintaining QoS. We evaluate the effectiveness of the OnDeGaS through simulation. The results show that the system is able to scale, while the average latency of the whole system is always maintained under an acceptable threshold. We also probe the benefits provided by the fault tolerance mechanism included in the system.

Performance prediction using an application-oriented mapping tool

Simulation frameworks are widely used to carry out performance predictions of parallel programs. In general, these environments do not support the use of automatic mapping mechanisms for assigning tasks to processors. We present a tool called pMAP (predicting the best mapping of parallel applications) that performs the mapping process of message-passing applications starting from the characterization of application behaviour. We show that it is important to explore in these simulation frameworks, not only how many resources are needed to achieve good results, but also how best to map the application onto the parallel system. We study the evaluation of the pMAP tool integrated with the commercial simulator DIMEMAS. The results show that for message-passing applications with different task structures, great improvements in the speedup can be obtained when simulations are carried out with the mappings generated by pMAP.

Improving multiple sequence alignment biological accuracy through genetic algorithms

Accuracy on multiple sequence alignments (MSA) is of great significance for such important biological applications as evolution and phylogenetic analysis, homology and domain structure prediction. In such analyses, alignment accuracy is crucial. In this paper, we investigate a combined scoring function capable of obtaining a good approximation to the biological quality of the alignment. The algorithm uses the information obtained by the different quality scores in order to improve the accuracy. The results show that the combined score is able to evaluate alignments better than the isolated scores.

Enhancing throughput for streaming applications running on cluster systems

The exploitation of throughput in a parallel application that processes an input data stream is a difficult challenge. For typical coarse-grain applications, where the computation time of tasks is greater than their communication time, the maximum achievable throughput is determined by the maximum task computation time. Thus, the improvement in throughput above this maximum would eventually require the modification of the source code of the tasks. In this work, we address the improvement of throughput by proposing two task replication methodologies that have the target throughput to be achieved as an input parameter. They proceed by generating a new task graph structure that permits the target throughput to be achieved. The first replication mechanism, named DPRM (Data Parallel Replication Mechanism), exploits the inner task data parallelism. The second mechanism, named TCRM (Task Copy Replication Mechanism), creates new execution paths inside the application task graph structure that allows more than one instance of data to be processed concurrently. We evaluate the effectiveness of these mechanisms with three real applications executed in a cluster system: the MPEG2 video compressor, the IVUS (Intra-Vascular Ultra-Sound) medical image application and the BASIZ (Bright and SAtured Images Zone) video processing application. In all these cases, the obtained throughput was greater after applying the proposed replication mechanism than what the application could provide with the original implementation.

Parallel calculation of volcanoes for cryptographic uses

Elliptic curve crypto systems are nowadays widely used in the design of many security devices. Nevertheless, since not every elliptic curve is useful for cryptographic purposes, mechanisms for providing good curves are highly needed. The generation of the volcano graph of elliptic curves can help to provide such good curves. However, this procedure turns out to be very expensive when performed sequentially. Hence, a parallel application for the calculation of such volcano graphs is proposed in this paper. In order to obtain high efficiency, a theoretical analysis is provided for obtaining an accurate granularity and for giving the appropriate number of tasks to be created. Experimental results show the benefits obtained in the speedup when executing the application in a cluster of workstations with message-passing for the generation of different volcano graphs. By the use of simulation, we study the scalability of the implementation and show that a speedup of more than 80 can be achieved in some cases