The Barabasi-Albert model (BA) is designed to generate scale-free networks using the preferential attachment mechanism. In the preferential attachment (PA) model, new nodes are sequentially introduced to the network and they attach preferentially to existing nodes. PA is a classical model with a natural intuition, great explanatory power and a simple mechanism. Therefore, PA is widely-used for network generation. However the sequential mechanism used in the PA model makes it an inefficient algorithm. The existing parallel approaches, on the other hand, suffer from either changing the original model or explicit complex low-level synchronization mechanisms. In this paper we investigate a high-level Actor-based model of the parallel algorithm of network generation and its scalable multicore implementation in Haskell.
Generation of social networks using Preferential Attachment (PA) mechanism is proposed in the Barabasi-Albert model. In this mechanism, new nodes are introduced to the network sequentially and they attach to the existing nodes preferentially where the preference can be based on the degree of the existing nodes. PA is a classical model with a natural intuition, great explanatory power and interesting mathematical properties. Some of these properties only appear in large-scale networks. However generation of such extra-large networks can be challenging due to memory limitations. In this paper, we investigate a distributedmemory approach for PA-based network generation which is scalable and which avoids low-level synchronization mechanisms thanks to utilizing a powerful programming model and proper programming constructs.
Abstract. In this paper we present an API to support modeling applications with Actors based on the paradigm of the Abstract Behavioural Specification (ABS) language. With the introduction of JAVA 8, we expose this API through a JAVA library to allow for a high-level actorbased methodology for programming distributed systems which supports the programming to interfaces discipline. We validate this solution through a case study where we obtain significant performance improvements as well as illustrating the ease with which simple high and low-level optimizations can be obtained by examining topologies and communication within an application. Using this API we show it is much easier to observe drawbacks of shared data-structures and communications methods in the design phase of a distributed application and apply the necessary corrections in order to obtain better results.
SUMMARYCloud environments have become a standard method for enterprises to offer their applications by means of web-services, data management systems or simply renting out computing resources. In our previous work we presented how we can use a modeling language together with the new features of JAVA 8 to overcome certain drawbacks of data structures and synchronization mechanisms in parallel applications. We extend this solution into a design pattern that allows application-specific optimizations in a distributed setting. We validate this integration using our previous case study of the Prime Sieve of Eratosthenes and illustrate the performance improvements in terms of speed-up and memory consumption.
In this paper we introduce a new programming model of multi-threaded actors
which feature the parallel processing of their messages. In this model an actor
consists of a group of active objects which share a message queue. We provide a
formal operational semantics, and a description of a Java-based implementation
for the basic programming abstractions describing multi-threaded actors.
Finally, we evaluate our proposal by means of an example application.Comment: In Proceedings ICE 2016, arXiv:1608.0313
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