Empirical Evaluation of the Parallel Distribution Sweeping Framework on Multicore Architectures

In this paper, we perform an empirical evaluation of the Parallel External Memory (PEM) model in the context of geometric problems. In particular, we implement the parallel distribution sweeping framework of Ajwani, Sitchinava and Zeh to solve batched 1-dimensional stabbing max problem. While modern processors consist of sophisticated memory systems (multiple levels of caches, set associativity, TLB, prefetching), we empirically show that algorithms designed in simple models, that focus on minimizing the I/O transfers between shared memory and single level cache, can lead to efficient software on current multicore architectures. Our implementation exhibits significantly fewer accesses to slow DRAM and, therefore, outperforms traditional approaches based on plane sweep and two-way divide and conquer.Comment: Longer version of ESA'13 pape

Fast Hierarchical Clustering and Other Applications of Dynamic Closest Pairs

We develop data structures for dynamic closest pair problems with arbitrary distance functions, that do not necessarily come from any geometric structure on the objects. Based on a technique previously used by the author for Euclidean closest pairs, we show how to insert and delete objects from an n-object set, maintaining the closest pair, in O(n log^2 n) time per update and O(n) space. With quadratic space, we can instead use a quadtree-like structure to achieve an optimal time bound, O(n) per update. We apply these data structures to hierarchical clustering, greedy matching, and TSP heuristics, and discuss other potential applications in machine learning, Groebner bases, and local improvement algorithms for partition and placement problems. Experiments show our new methods to be faster in practice than previously used heuristics.Comment: 20 pages, 9 figures. A preliminary version of this paper appeared at the 9th ACM-SIAM Symp. on Discrete Algorithms, San Francisco, 1998, pp. 619-628. For source code and experimental results, see http://www.ics.uci.edu/~eppstein/projects/pairs

An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development

In this paper, we investigate model-driven engineering, reporting on an exploratory case-study conducted at a large automotive company. The study consisted of interviews with 20 engineers and managers working in different roles. We found that, in the context of a large organization, contextual forces dominate the cognitive issues of using model-driven technology. The four forces we identified that are likely independent of the particular abstractions chosen as the basis of software development are the need for diffing in software product lines, the needs for problem-specific languages and types, the need for live modeling in exploratory activities, and the need for point-to-point traceability between artifacts. We also identified triggers of accidental complexity, which we refer to as points of friction introduced by languages and tools. Examples of the friction points identified are insufficient support for model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe

Online Course on Potato Production for Georgia: Final Technical Report (FTR)

The Online Course on Potato Production for Georgia was held to strengthen the potato seed production capacities of local and national technicians in the USAID Potato Program in Georgia. The virtual course was funded by USAID and organized by the International Potato Center (CIP) covering the following topics: pest and disease management, seed production, and fertilizer and water management. The course was organized around six online webinars and six discussion sessions using CIP’s Talent MS platform. Each webinar and discussion session took between 60 and 90 minutes. The online webinars included a pre-recorded presentation and a Q&A session led by the course instructors. The webinars were prepared in English by the course instructors (with input from the course organizers) and were translated (text and voice over) into the Georgian language. The discussion sessions mainly included panels, with the instructors asking questions to stimulate discussion, and responses from the participants or students (farmers, business people, extensionists and researchers). There was simultaneous English-Georgian translation for all Q&A and discussion sessions. About half of the course participants were women. The online webinars were held over six consecutive weeks (1 June—7 July), usually on Tuesdays (two webinars were held on Wednesdays). The discussion sessions took place that same week on Thursday. A 10-question, multiple-choice test was given at the start of each webinar and near the end of each discussion session (one unique test each week) to judge how well the participants mastered the course material. Students who attended at least five webinars and five discussion sessions received a certificate of participation. The six units were: Unit 1: Integrated management of late blight - Wilmer Pérez Unit 2: Integrated management of viral diseases - Segundo Fuentes Unit 3: Plant nutrition and fertilizer management – Elke Vandamme Unit 4: Postharvest and seed potato storage – André Devaux Unit 5: Production of seed potato - Jorge Andrade-Piedra Unit 6: Irrigation and water management – David Ramírez and Javier Rinza At the end of week 6, the participants evaluated the course, suggesting that they thought that the content, instructors and format were of high quality

Managing Linguistic Data Summaries in Advanced P2P Applications

chapitre... à corrigerAs the amount of stored data increases, data localization techniques become no longer sufficient in P2P systems. A practical approach is to rely on compact database summaries rather than raw database records, whose access is costly in large P2P systems. In this chapter, we describe a solution for managing linguistic data summaries in advanced P2P applications which are dealing with semantically rich data. The produced summaries are synthetic, multidimensional views over relational tables. The novelty of this proposal relies on the double summary exploitation in distributed P2P systems. First, as semantic indexes, they support locating relevant nodes based on their data descriptions. Second, due to their intelligibility, these summaries can be directly queried and thus approximately answer a query without the need for exploring original data. The proposed solution consists first in defining a summary model for hierarchical P2P systems. Second, appropriate algorithms for summary creation and maintenance are presented. A query processing mechanism, which relies on summary querying, is then proposed to demonstrate the benefits that might be obtained from summary exploitation

Case studies of Roots, Tubers and Bananas seed systems.

The seed systems of RTB (root, tuber, and banana) crops are unique because they are propagated from vegetative parts of the plant, not from true seed. RTB seed is thus bulkier, more perishable, and more subject to the attacks of pests and diseases than is true seed. Because of this, there is often a gap between potential and real crop yields, which seed interventions seek to narrow. Seed systems are formal or informal networks of people and organizations that produce, plant, and distribute seed. Informal systems may deliver low quality seed, but not always. This book describes 13 RTB seed system interventions, using a framework based on the concepts of seed availability, access, and quality. The 13 case studies included (1) a potato-growers’ association in Ecuador, (2) a hydroponic seed potato in Peru, (3) a yam seed technology in Nigeria, (4) a banana and plantain project in Ghana, (5) a sweetpotato seed project in Tanzania and (6) one in Rwanda, (7) a seed potato system in Kenya, (8) cassava in Nicaragua, (9) seed potato in Malawi, (10) disease-resistant cassava varieties in seven African countries, (11) a tissue culture banana project, (12) an emergency plantain and banana project in East Africa, and (13) a large cassava seed project in six African countries

Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization

International audienceThe use of Reinforcement Learning in real-world scenarios is strongly limited by issues of scale. Most RL learning algorithms are unable to deal with problems composed of hundreds or sometimes even dozens of possible actions, and therefore cannot be applied to many real-world problems. We consider the RL problem in the supervised classification framework where the optimal policy is obtained through a multiclass classifier, the set of classes being the set of actions of the problem. We introduce error-correcting output codes (ECOCs) in this setting and propose two new methods for reducing complexity when using rollouts-based approaches. The first method consists in using an ECOC-based classifier as the multiclass classifier, reducing the learning complexity from O(A2) to O(Alog(A)) . We then propose a novel method that profits from the ECOC's coding dictionary to split the initial MDP into O(log(A)) separate two-action MDPs. This second method reduces learning complexity even further, from O(A2) to O(log(A)) , thus rendering problems with large action sets tractable. We finish by experimentally demonstrating the advantages of our approach on a set of benchmark problems, both in speed and performance

Efficient Processing of Spatial Joins Using R-Trees

Abstract: In this paper, we show that spatial joins are very suitable to be processed on a parallel hardware platform. The parallel system is equipped with a so-called shared virtual memory which is well-suited for the design and implementation of parallel spatial join algorithms. We start with an algorithm that consists of three phases: task creation, task assignment and parallel task execu-tion. In order to reduce CPU- and I/O-cost, the three phases are processed in a fashion that pre-serves spatial locality. Dynamic load balancing is achieved by splitting tasks into smaller ones and reassigning some of the smaller tasks to idle processors. In an experimental performance compar-ison, we identify the advantages and disadvantages of several variants of our algorithm. The most efficient one shows an almost optimal speed-up under the assumption that the number of disks is sufficiently large. Topics: spatial database systems, parallel database systems