Data accesses consume considerable execution time during program execution. If we can improve the data access time at compile time, overall program execution time can be improved effectively. Hence, we designed a software for a data locality estimation method for estimating data locality in program optimizer. The program optimizer can then reduce the number of main memory block access and enhance the overall program performance effectively. In this research, we implemented the software design of the data locality estimation method. It includes two estimation models for estimating the number of access matches in memory blocks and for estimating the number of memory block access. We carried out experiments to verify accuracy of the locality estimation method.

Heap memory allocation plays an important role in modern applications. Conventional heap allocators, however, generally ignore the underlying memory hierarchy of the system, favoring instead a low runtime overhead and fast response times. Unfortunately, with little concern for the memory hierarchy, the data layout may exhibit poor spatial locality, and degrade cache performance. In this paper, we describe a dynamic heap allocation scheme called pool allocation. The strategy aims to improve cache performance by inspecting memory allocation requests, and allocating memory from appropriate heap pools as dictated by the requesting context. The advantages are two fold. First, by pooling together data with a common context, we expect to improve spatial locality, as data fetched to the caches will contain fewer items from different contexts. If the allocation patterns are closely matched to the traversal patterns, the end result is faster memory performance. Second, by pooling heap objects, we expect access patterns to exhibit more regularity, thus creating more opportunities for data prefetching. Our dynamic memory optimizer exploits the increased regularity to insert prefetch instructions at runtime. The optimizations are implemented in DynamoRIO, a dynamic optimization framework. We evaluate the work using various benchmarks, and measure a 17% speedup over gcc -O3 on an Athlon MP, and a 13% speedup on a Pentium 4. / Singapore-MIT Alliance (SMA)

We present new approaches to define and analyze geometric graphs. The region-counting distances, introduced by Demaine, Iacono and Langerman, associate to any pair of points (p,q) the number of items of a dataset S contained in a region R(p,q) surrounding (p,q). We define region-counting disks and circles, and study the complexity of these objects. Algorithms to compute epsilon-approximations of region-counting distances and approximations of region-counting circles are presented. We propose a definition of the locality for properties of geometric graphs. We measure the local density of graphs using the region-counting distances between pairs of vertices, and we use this density to define local properties of classes of graphs. We illustrate the locality by introducing the local diameter of geometric graphs: we define it as the upper bound on the size of the shortest path between any pair of vertices, expressed as a function of the density of the graph around those vertices. We determine the local diameter of several well-studied graphs such as the Theta-graph, the Ordered Theta-graph and the Skip List Spanner. We also show that various operations, such as path and point queries using geometric graphs as data structures, have complexities which can be expressed as local properties. A family of proximity graphs, called Empty Region Graphs (ERG) is presented. The vertices of an ERG are points in the plane, and two points are connected if their neighborhood, defined by a region, does not contain any other point. The region defining the neighborhood of two points is a parameter of the graph. This family of graphs includes several known proximity graphs such as Nearest Neighbor Graphs, Beta-Skeletons or Theta-Graphs. We concentrate on ERGs that are invariant under translations, rotations and uniform scaling of the vertices. We give conditions on the region defining an ERG to ensure a number of properties that might be desirable in applications, such as planarity, connectivity, triangle-freeness, cycle-freeness, bipartiteness and bounded degree. These conditions take the form of what we call tight regions: maximal or minimal regions that a region must contain or be contained in to make the graph satisfy a given property. We show that every monotone property has at least one corresponding tight region; we discuss possibilities and limitations of this general model for constructing a graph from a point set. We introduce and analyze sigma-local graphs, based on a definition of locality by Erickson, to illustrate efficient construction algorithm on a subclass of ERGs.

No description available.

The aim of my thesis is to show that some properties of rightward movement constructions (a cover term referring to sentences where an element appears to be “displaced” to the right) may be derived from syntactic principles and interface conditions within the framework of the minimalist program, and also to claim that properties which have up to now been dealt with purely in syntax receive a better account in terms of language processing. I develop a nonmovement approach to the Japanese Post-Verbal Construction (JPVC) by claiming that a postverbal phrase is adjoined to an element by External Merge, and that it is permitted as a syntactic object by a licensing condition which allows it to be construed as an argument or a modifier by interpretive rules at the interface level (SEM/LF). Many syntactic properties of the JPVC are accounted for in terms of independently motivated interface conditions and syntactic principles. I assume that the parser is a system that can make use of UG principles as well as language particular rules, and that the parser should be universal. The interaction of syntactic principles with parsing strategies makes it possible to cope with elusive problems concerning scope ambiguity as well as locality effects observed in the JPVC. This interaction may also account for the Right Roof Constraint effect displayed by the rightward movement constructions in English (i.e., Heavy "P Shift (H"PS), Extraposition from "P, and Right Dislocation). Furthermore, it predicts that languages fall into three types with respect to the possibility of the HNPS construction: (i) both subjects and objects can appear in postverbal position (e.g., Italian, Japanese, Turkish); (ii) subjects cannot do so (e.g., English); (iii) neither subjects nor objects can appear in postverbal position (e.g., Dutch, German). The claim that there is a parsing strategy relating to linear distance is supported by an experiment designed as a test for the effect of the length of intervening elements on acceptability of the JPVC, with the data obtained using Magnitude Estimation, a technique used in psychophysics to measure judgements of sensory stimuli.

Career guidance is a core element of labour market and education policy. Young people’s transitions from education to employment need support through active career guidance. This body of research examines aspects of place and partnership working as it applies to career policy and practice for young people with a particular focus on the role of schools. The engagement of diverse partners from different sectors and interests has become an essential element of public policy and its implementation. To understand partnership working it is critical to pay attention to the relationship between the selection of partners, their combined remit, the scale of their activities and the diverse places in which they emerge. Many of the issues that policy attempts to address are also shaped by, and in, the places in which they are experienced. The research informing these papers has been undertaken as either academic research projects or as funded research over more than two decades. Many have used place-based case studies. The overall finding of this is that deliberative multi-partner engagement has become essential to the provision of pathways to the labour market that would otherwise be blocked for some young people. The centre of gravity in these discussions is the school. As organisations with a geographic footprint, the active engagement of schools in partnerships builds infrastructures, pathways and new spaces of engagement that help their pupils understand the work place. Through the twin policy paths of territorial economic development policy and a progressive socio-political approach to career guidance, policy makers have endowed schools with this responsibility. Schools are spaces of engagement with a wider world and simultaneously they are places that reflect their economic, social and cultural context. Their role as partner and place-maker needs acknowledgement within any national careers strategy that hopes to connect a spatially sensitive industrial policy with a locally enacted careers and labour market policy.

Dynamic memory allocators are a determining factor of an application's performanceand have the opportunity to improve a major performance bottleneck ontoday's computer hardware: data locality. To approach this problem, a memoryallocator must rst oer strategies that allow the locality problem to be addressed.However, while focusing on locality, an allocator must also not ignore the existing constraintsof allocation speed and fragmentation, which further complicate its design. Inorder for a locality improving technique to be successfully employed in today's largecode applications, its integration needs to be automatic, without user intervention.The alternative, manual integration, is not a tractable solution.In this dissertation we develop three novel memory allocators that explore dierentallocation strategies that enhance an application's locality. We conduct the rststudy that shows that allocation speed, fragmentation and locality improving goalsare antagonistic. We develop an automatic method that supplies allocation hintsfrom C++ STL containers to their allocators. This method allows applications tobenet from locality improving techniques at the cost of a simple re-compilation. Weconduct the rst study that quanties the eect of allocation hints on performance,and show that an allocator with high locality of reference can be as competitive asone using an application's spatial feedback.To further allow dynamic memory allocation to improve an application's performance,new and non-traditional strategies need be explored. We develop a generic software tool that allows users to examine unconventional strategies. The tool allowsusers not only to focus on allocation strategies rather than their implementation, butalso to compare and contrast various approaches.

Dynamic memory allocators are a determining factor of an application's performanceand have the opportunity to improve a major performance bottleneck ontoday's computer hardware: data locality. To approach this problem, a memoryallocator must rst oer strategies that allow the locality problem to be addressed.However, while focusing on locality, an allocator must also not ignore the existing constraintsof allocation speed and fragmentation, which further complicate its design. Inorder for a locality improving technique to be successfully employed in today's largecode applications, its integration needs to be automatic, without user intervention.The alternative, manual integration, is not a tractable solution.In this dissertation we develop three novel memory allocators that explore dierentallocation strategies that enhance an application's locality. We conduct the rststudy that shows that allocation speed, fragmentation and locality improving goalsare antagonistic. We develop an automatic method that supplies allocation hintsfrom C++ STL containers to their allocators. This method allows applications tobenet from locality improving techniques at the cost of a simple re-compilation. Weconduct the rst study that quanties the eect of allocation hints on performance,and show that an allocator with high locality of reference can be as competitive asone using an application's spatial feedback.To further allow dynamic memory allocation to improve an application's performance,new and non-traditional strategies need be explored. We develop a generic software tool that allows users to examine unconventional strategies. The tool allowsusers not only to focus on allocation strategies rather than their implementation, butalso to compare and contrast various approaches.

No description available.

The immune system has the ability to discriminate self from non-self proteins and also make appropriate immune responses to pathogens. A fundamental problem is to understand the genomic differences and similarities among the sets of self peptides and non-self peptides. The sequencing of human, mouse and numerous pathogen genomes and cataloging of their respective proteomes allows host self and non-self peptides to be identified. T-cells make this determination at the peptide level based on peptides displayed by MHC molecules.<p>In this project, peptides of specific lengths (k-mers) are generated from each protein in the proteomes of various model organisms. The set of unique k-mers for each species is stored in a library and defines its "immunological self". Using the libraries, organisms can be compared to determine the levels of peptide overlap. The observed levels of overlap can also be compared with levels which can be expected "at random" and statistical conclusions drawn.<p>A problem with this procedure is that sequence information in public protein databases (Swiss-PROT, UniProt, PIR) often contains ambiguities. Three strategies for dealing with such ambiguities have been explored in earlier work and the strategy of removing ambiguous k-mers is used here.<p>Peptide fragments (k-mers) which elicit immune responses are often localized within the sequences of proteins from pathogens. These regions are known as "immunodominants" (i.e., hot spots) and are important in immunological work. After investigating the peptide universes and their overlaps, the question of whether known regions of immunological significance (e.g., epitope) come from regions of low host-similarity is explored. The known regions of epitopes are compared with the regions of low host-similarity (i.e., non-overlaps) between HIV-1 and human proteomes at the 7-mer level. Results show that the correlation between these two regions is not statistically significant. In addition, pairs involving human and human viruses are explored. For these pairs, one graph for each k-mer level is generated showing the actual numbers of matches between organisms versus the expected numbers. From graphs for 5-mer and 6-mer level, we can see that the number of overlapping occurrences increases as the size of the viral proteome increases.<p>A detailed investigation of the overlaps/non-overlaps between viral proteome and human proteome reveals that the distribution of the locations of these overlaps/non-overlaps may have "structure" (e.g. locality clustering). Thus, another question that is explored is whether the locality clustering is statistically significant. A chi-square analysis is used to analyze the locality clustering. Results show that the locality clusterings for HIV-1, HIV-2 and Influenza A virus at the 5-mer, 6-mer and 7-mer levels are statistically significant. Also, for self-similarity of human protein Desmoglein 3 to the remaining human proteome, it shows that the locality clustering is not statistically significant at the 5-mer level while it is at the 6-mer and 7-mer levels.