Constructs and evaluation strategies for intelligent speculative parallelism - armageddon revisited

This report addresses speculative parallelism (the assignment of spare processing resources to tasks which are not known to be strictly required for the successful completion of a computation) at the user and application level. At this level, the execution of a program is seen as a (dynamic) tree —a graph, in general. A solution for a problem is a traversal of this graph from the initial state to a node known to be the answer. Speculative parallelism then represents the assignment of resources to múltiple branches of this graph even if they are not positively known to be on the path to a solution. In highly non-deterministic programs the branching factor can be very high and a naive assignment will very soon use up all the resources. This report presents work assignment strategies other than the usual depth-first and breadth-first. Instead, best-first strategies are used. Since their definition is application-dependent, the application language contains primitives that allow the user (or application programmer) to a) indícate when intelligent OR-parallelism should be used; b) provide the functions that define "best," and c) indícate when to use them. An abstract architecture enables those primitives to perform the search in a "speculative" way, using several processors, synchronizing them, killing the siblings of the path leading to the answer, etc. The user is freed from worrying about these interactions. Several search strategies are proposed and their implementation issues are addressed. "Armageddon," a global pruning method, is introduced, together with both a software and a hardware implementation for it. The concepts exposed are applicable to áreas of Artificial Intelligence such as extensive expert systems, planning, game playing, and in general to large search problems. The proposed strategies, although showing promise, have not been evaluated by simulation or experimentation.

Win-Win transport strategies: searching for synergies.

The need of an urban transport strategy on urban areas which solves the environmental problems derived from traffic without decreasing the trip attraction of these urban areas is taken for granted. Besides there is also a clear consensus among researchers and institutions in the need for integrated transport strategies (May et al., 2006; Zhang et al., 2006). But there is still a lack of knowledge on the policy measures to be implemented. This research aims to deepen in the understanding of how do different measures interact when implemented together: synergies and complementarities between them. The methodological approach to achieve this objective has been the double analysis ? quantitative and comprehensive ? of the different impacts produced, first of all by each of the measures by itself, and later on combining these measures. For this analysis, we have first defined the objectives to achieve within the transport strategy ? emissions and noise decrease without losing trip attraction - , and then selecting the measures to test the effects these objectives generate. This selection has been based on a literature review, searching for measures with have proven to be successful in achieving at least one of the objectives. The different policies and policy combinations have been tested in a multimodal transport model, considering the city of Madrid as case study. The final aim of the research is to find a transport strategy which produces positive impact in all the objectives established, this is a win-win strategy.

Component integration strategies in metamorphic 4-junction III-V concentrator solar cells

Progressing beyond 3-junction inverted-metamorphic multijunction solar cells grown on GaAs substrates, to 4-junction devices, requires the development of high quality metamorphic 0.7 eV GaInAs solar cells. Once accomplished, the integration of this subcell into a full, Monolithic, series connected, 4J-IMM structure demands the development of a metamorphic tunnel junction lattice matched to the 1eV GaInAs subcell. Moreover, the 0.7 eV junction adds about 2 hours of growth time to the structure, implying a heavier annealing of the subcells and tunnel junctions grown first. The final 4J structure is above 20 Pm thick, with about half of this thickness used by the metamorphic buffers required to change the lattice constant throughout the structure. Thinning of these buffers would help reduce the total thickness of the 4J structure to decrease its growth cost and the annealing time. These three topics: development of a metamorphic tunnel junction for the 4th junction, analysis of the annealing, and thinning of the structure, are tackled in this work. The results presented show the successful implementation of an antimonide-based tunnel junction for the 4th junction and of pathways to mitigate the impact of annealing and reduce the thickness of the metamorphic buffers.