Complementing user-level coarse-grain parallelism with implicit speculative parallelism

Multi-core and many-core systems are the norm in contemporary processor technology and are expected to remain so for the foreseeable future. Parallel programming is, thus, here to stay and programmers have to endorse it if they are to exploit such systems for their applications. Programs using parallel programming primitives like PThreads or OpenMP often exploit coarse-grain parallelism, because it offers a good trade-off between programming effort versus performance gain. Some parallel applications show limited or no scaling beyond a number of cores. Given the abundant number of cores expected in future many-cores, several cores would remain idle in such cases while execution performance stagnates. This thesis proposes using cores that do not contribute to performance improvement for running implicit fine-grain speculative threads. In particular, we present a many-core architecture and protocols that allow applications with coarse-grain explicit parallelism to further exploit implicit speculative parallelism within each thread. We show that complementing parallel programs with implicit speculative mechanisms offers significant performance improvements for a large and diverse set of parallel benchmarks. Implicit speculative parallelism frees the programmer from the additional effort to explicitly partition the work into finer and properly synchronized tasks. Our results show that, for a many-core comprising 128 cores supporting implicit speculative parallelism in clusters of 2 or 4 cores, performance improves on top of the highest scalability point by 44% on average for the 4-core cluster and by 31% on average for the 2-core cluster. We also show that this approach often leads to better performance and energy efficiency compared to existing alternatives such as Core Fusion and Turbo Boost. Moreover, we present a dynamic mechanism to choose the number of explicit and implicit threads, which performs within 6% of the static oracle selection of threads. To improve energy efficiency processors allow for Dynamic Voltage and Frequency Scaling (DVFS), which enables changing their performance and power consumption on-the-fly. We evaluate the amenability of the proposed explicit plus implicit threads scheme to traditional power management techniques for multithreaded applications and identify room for improvement. We thus augment prior schemes and introduce a novel multithreaded power management scheme that accounts for implicit threads and aims to minimize the Energy Delay2 product (ED2). Our scheme comprises two components: a “local” component that tries to adapt to the different program phases on a per explicit thread basis, taking into account implicit thread behavior, and a “global” component that augments the local components with information regarding inter-thread synchronization. Experimental results show a reduction of ED2 of 8% compared to having no power management, with an average reduction in power of 15% that comes at a minimal loss of performance of less than 3% on average

MapReduce network enabled algorithms for classification based on association rules

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.There is growing evidence that integrating classification and association rule mining can produce more efficient and accurate classifiers than traditional techniques. This thesis introduces a new MapReduce based association rule miner for extracting strong rules from large datasets. This miner is used later to develop a new large scale classifier. Also new MapReduce simulator was developed to evaluate the scalability of proposed algorithms on MapReduce clusters. The developed associative rule miner inherits the MapReduce scalability to huge datasets and to thousands of processing nodes. For finding frequent itemsets, it uses hybrid approach between miners that uses counting methods on horizontal datasets, and miners that use set intersections on datasets of vertical formats. The new miner generates same rules that usually generated using apriori-like algorithms because it uses the same confidence and support thresholds definitions. In the last few years, a number of associative classification algorithms have been proposed, i.e. CPAR, CMAR, MCAR, MMAC and others. This thesis also introduces a new MapReduce classifier that based MapReduce associative rule mining. This algorithm employs different approaches in rule discovery, rule ranking, rule pruning, rule prediction and rule evaluation methods. The new classifier works on multi-class datasets and is able to produce multi-label predications with probabilities for each predicted label. To evaluate the classifier 20 different datasets from the UCI data collection were used. Results show that the proposed approach is an accurate and effective classification technique, highly competitive and scalable if compared with other traditional and associative classification approaches. Also a MapReduce simulator was developed to measure the scalability of MapReduce based applications easily and quickly, and to captures the behaviour of algorithms on cluster environments. This also allows optimizing the configurations of MapReduce clusters to get better execution times and hardware utilization

The future of dialects: Selected papers from Methods in Dialectology XV

Traditional dialects have been encroached upon by the increasing mobility of their speakers and by the onslaught of national languages in education and mass media. Typically, older dialects are “leveling” to become more like national languages. This is regrettable when the last articulate traces of a culture are lost, but it also promotes a complex dynamics of interaction as speakers shift from dialect to standard and to intermediate compromises between the two in their forms of speech. Varieties of speech thus live on in modern communities, where they still function to mark provenance, but increasingly cultural and social provenance as opposed to pure geography. They arise at times from the need to function throughout the different groups in society, but they also may have roots in immigrants’ speech, and just as certainly from the ineluctable dynamics of groups wishing to express their identity to themselves and to the world. The future of dialects is a selection of the papers presented at Methods in Dialectology XV, held in Groningen, the Netherlands, 11-15 August 2014. While the focus is on methodology, the volume also includes specialized studies on varieties of Catalan, Breton, Croatian, (Belgian) Dutch, English (in the US, the UK and in Japan), German (including Swiss German), Italian (including Tyrolean Italian), Japanese, and Spanish as well as on heritage languages in Canada

The future of dialects: Selected papers from Methods in Dialectology XV

Traditional dialects have been encroached upon by the increasing mobility of their speakers and by the onslaught of national languages in education and mass media. Typically, older dialects are “leveling” to become more like national languages. This is regrettable when the last articulate traces of a culture are lost, but it also promotes a complex dynamics of interaction as speakers shift from dialect to standard and to intermediate compromises between the two in their forms of speech. Varieties of speech thus live on in modern communities, where they still function to mark provenance, but increasingly cultural and social provenance as opposed to pure geography. They arise at times from the need to function throughout the different groups in society, but they also may have roots in immigrants’ speech, and just as certainly from the ineluctable dynamics of groups wishing to express their identity to themselves and to the world. The future of dialects is a selection of the papers presented at Methods in Dialectology XV, held in Groningen, the Netherlands, 11-15 August 2014. While the focus is on methodology, the volume also includes specialized studies on varieties of Catalan, Breton, Croatian, (Belgian) Dutch, English (in the US, the UK and in Japan), German (including Swiss German), Italian (including Tyrolean Italian), Japanese, and Spanish as well as on heritage languages in Canada