Fault-tolerant dynamic parallel schedules

Dynamic Parallel Schedules (DPS) is a high-level framework for developing parallel applications on distributed memory computers such as clusters of PCs. DPS applications are defined by using directed acyclic flow graphs composed of user-defined operations. These operations derive from basic concepts provided by the framework: split, merge, leaf and stream operations. Whereas a simple parallel application can be expressed with a split-leaf-merge sequence of operations, flow graphs of arbitrary complexity can be created. DPS provides run-time support for dynamically mapping flow graph operations onto the nodes of a cluster. The flow graph based application description used in DPS allows the framework to offer many additional features, most of these transparently to the application developer. In order to maximize performance, DPS applications benefit from automatic overlapping of computations and communications and from implicit pipelining. The framework provides simple primitives for flow control and load balancing. Applications can integrate flow graph parts provided by other applications as parallel components. Since the mapping of DPS applications to processing nodes can be dynamically changed at runtime, DPS provides a basis for developing malleable applications. The DPS framework provides a complete fault tolerance mechanism based on the dynamic mapping capabilities, ensuring continued execution of parallel applications even in the presence of multiple node failures. DPS is provided as an open-source, cross-platform C++ library allowing DPS applications and services to run on heterogeneous clusters

Subheap-Augmented Garbage Collection

Automated memory management avoids the tedium and danger of manual techniques. However, as no programmer input is required, no widely available interface exists to permit principled control over sometimes unacceptable performance costs. This dissertation explores the idea that performance-oriented languages should give programmers greater control over where and when the garbage collector (GC) expends effort. We describe an interface and implementation to expose heap partitioning and collection decisions without compromising type safety. We show that our interface allows the programmer to encode a form of reference counting using Hayes\u27 notion of key objects. Preliminary experimental data suggests that our proposed mechanism can avoid high overheads suffered by tracing collectors in some scenarios, especially with tight heaps. However, for other applications, the costs of applying subheaps---in human effort and runtime overheads---remain daunting

An automated OpenCL FPGA compilation framework targeting a configurable, VLIW chip multiprocessor

Modern system-on-chips augment their baseline CPU with coprocessors and accelerators to increase overall computational capacity and power efficiency, and thus have evolved into heterogeneous systems. Several languages have been developed to enable this paradigm shift, including CUDA and OpenCL. This thesis discusses a unified compilation environment to enable heterogeneous system design through the use of OpenCL and a customised VLIW chip multiprocessor (CMP) architecture, known as the LE1. An LLVM compilation framework was researched and a prototype developed to enable the execution of OpenCL applications on the LE1 CPU. The framework fully automates the compilation flow and supports work-item coalescing to better utilise the CPU cores and alleviate the effects of thread divergence. This thesis discusses in detail both the software stack and target hardware architecture and evaluates the scalability of the proposed framework on a highly precise cycle-accurate simulator. This is achieved through the execution of 12 benchmarks across 240 different machine configurations, as well as further results utilising an incomplete development branch of the compiler. It is shown that the problems generally scale well with the LE1 architecture, up to eight cores, when the memory system becomes a serious bottleneck. Results demonstrate superlinear performance on certain benchmarks (x9 for the bitonic sort benchmark with 8 dual-issue cores) with further improvements from compiler optimisations (x14 for bitonic with the same configuration

Improving Data Structures and Algorithms

This thesis addresses important algorithms and data structures used in sequence analysis for applications such as read mapping. First, we give an overview on state-of-the-art FM indices and present the latest improvements. In particular, we will introduce a recently published FM index based on a new data structure: EPR dictionaries. This rank data structures allows search steps in constant time for unidirectional and bidirectional FM indices. To our knowledge this is the first and only constant-time implementation of a bidirectional FM index at the time of writing. We show that its running time is not only optimal in theory, but currently also outperforms all available FM index implementations in practice. Second, we cover approximate string matching in bidirectional indices. To improve the running time and make higher error rates suitable for index-based searches, we introduce an integer linear program for finding optimal search strategies. We show that it is significantly faster than other search strategies in indices and cover additional improvements such as hybrid approaches of index-based searches with in-text verification, i.e., at some point the partially matched string is located and verified directly in the text. Finally, we present a yet unpublished algorithm for fast computation of the mappability of genomic sequences. Mappability is a measure for the uniqueness of a genome by counting how often each $k$-mer of the sequence occurs with a certain error threshold in the genome itself. We suggest two applications of mappability with prototype implementations: First, a read mapper incorporating the mappability information to improve the running time when mapping reads that match highly repetitive regions, and second, we use the mappability information to identify phylogenetic markers in a set of similar strains of the same species by the example of E. coli. Unique regions allow identifying and distinguishing even highly similar strains using unassembled sequencing data. The findings in this thesis can speed up many applications in bioinformatics as we demonstrate for read mapping and computation of mappability, and give suggestions for further research in this field

Transform Based And Search Aware Text Compression Schemes And Compressed Domain Text Retrieval

In recent times, we have witnessed an unprecedented growth of textual information via the Internet, digital libraries and archival text in many applications. While a good fraction of this information is of transient interest, useful information of archival value will continue to accumulate. We need ways to manage, organize and transport this data from one point to the other on data communications links with limited bandwidth. We must also have means to speedily find the information we need from this huge mass of data. Sometimes, a single site may also contain large collections of data such as a library database, thereby requiring an efficient search mechanism even to search within the local data. To facilitate the information retrieval, an emerging ad hoc standard for uncompressed text is XML which preprocesses the text by putting additional user defined metadata such as DTD or hyperlinks to enable searching with better efficiency and effectiveness. This increases the file size considerably, underscoring the importance of applying text compression. On account of efficiency (in terms of both space and time), there is a need to keep the data in compressed form for as much as possible. Text compression is concerned with techniques for representing the digital text data in alternate representations that takes less space. Not only does it help conserve the storage space for archival and online data, it also helps system performance by requiring less number of secondary storage (disk or CD Rom) accesses and improves the network transmission bandwidth utilization by reducing the transmission time. Unlike static images or video, there is no international standard for text compression, although compressed formats like .zip, .gz, .Z files are increasingly being used. In general, data compression methods are classified as lossless or lossy. Lossless compression allows the original data to be recovered exactly. Although used primarily for text data, lossless compression algorithms are useful in special classes of images such as medical imaging, finger print data, astronomical images and data bases containing mostly vital numerical data, tables and text information. Many lossy algorithms use lossless methods at the final stage of the encoding stage underscoring the importance of lossless methods for both lossy and lossless compression applications. In order to be able to effectively utilize the full potential of compression techniques for the future retrieval systems, we need efficient information retrieval in the compressed domain. This means that techniques must be developed to search the compressed text without decompression or only with partial decompression independent of whether the search is done on the text or on some inversion table corresponding to a set of key words for the text. In this dissertation, we make the following contributions: (1) Star family compression algorithms: We have proposed an approach to develop a reversible transformation that can be applied to a source text that improves existing algorithm\u27s ability to compress. We use a static dictionary to convert the English words into predefined symbol sequences. These transformed sequences create additional context information that is superior to the original text. Thus we achieve some compression at the preprocessing stage. We have a series of transforms which improve the performance. Star transform requires a static dictionary for a certain size. To avoid the considerable complexity of conversion, we employ the ternary tree data structure that efficiently converts the words in the text to the words in the star dictionary in linear time. (2) Exact and approximate pattern matching in Burrows-Wheeler transformed (BWT) files: We proposed a method to extract the useful context information in linear time from the BWT transformed text. The auxiliary arrays obtained from BWT inverse transform brings logarithm search time. Meanwhile, approximate pattern matching can be performed based on the results of exact pattern matching to extract the possible candidate for the approximate pattern matching. Then fast verifying algorithm can be applied to those candidates which could be just small parts of the original text. We present algorithms for both k-mismatch and k-approximate pattern matching in BWT compressed text. A typical compression system based on BWT has Move-to-Front and Huffman coding stages after the transformation. We propose a novel approach to replace the Move-to-Front stage in order to extend compressed domain search capability all the way to the entropy coding stage. A modification to the Move-to-Front makes it possible to randomly access any part of the compressed text without referring to the part before the access point. (3) Modified LZW algorithm that allows random access and partial decoding for the compressed text retrieval: Although many compression algorithms provide good compression ratio and/or time complexity, LZW is the first one studied for the compressed pattern matching because of its simplicity and efficiency. Modifications on LZW algorithm provide the extra advantage for fast random access and partial decoding ability that is especially useful for text retrieval systems. Based on this algorithm, we can provide a dynamic hierarchical semantic structure for the text, so that the text search can be performed on the expected level of granularity. For example, user can choose to retrieve a single line, a paragraph, or a file, etc. that contains the keywords. More importantly, we will show that parallel encoding and decoding algorithm is trivial with the modified LZW. Both encoding and decoding can be performed with multiple processors easily and encoding and decoding process are independent with respect to the number of processors

Curve-Based Shape Matching Methods and Applications

One of the main cues we use in our everyday life when interacting with the environment is shape. For example, we use shape information to recognise a chair, grasp a cup, perceive traffic signs and solve jigsaw puzzles. We also use shape when dealing with more sophisticated tasks, such as the medical diagnosis of radiographs or the restoration of archaeological artifacts. While the perception of shape and its use is a natural ability of human beings, endowing machines with such skills is not straightforward. However, the exploitation of shape cues is important for the development of competent computer methods that will automatically perform tasks such as those just mentioned. With this aim, the present work proposes computer methods which use shape to tackle two important tasks, namely packing and object recognition. The packing problem arises in a variety of applications in industry, where the placement of a set of two-dimensional shapes on a surface such that no shapes overlap and the uncovered surface area is minimised is important. Given that this problem is NP-complete, we propose a heuristic method which searches for a solution of good quality, though not necessarily the optimal one, within a reasonable computation time. The proposed method adopts a pictorial representation and employs a greedy algorithm which uses a shape matching module in order to dynamically select the order and the pose of the parts to be placed based on the “gaps” appearing in the layout during the execution. This thesis further investigates shape matching in the context of object recognition and first considers the case where the target object and the input scene are represented by their silhouettes. Two distinct methods are proposed; the first method follows a local string matching approach, while the second one adopts a global optimisation approach using dynamic programming. Their use of silhouettes, however, rules out the consideration of any internal contours that might appear in the input scene, and in order to address this limitation, we later propose a graph-based scheme that performs shape matching incorporating information from both internal and external contours. Finally, we lift the assumption made that input data are available in the form of closed curves, and present a method which can robustly perform object recognition using curve fragments (edges) as input evidence. Experiments conducted with synthetic and real images, involving rigid and deformable objects, show the robustness of the proposed methods with respect to geometrical transformations, heavy clutter and substantial occlusion

Index to 1981 NASA Tech Briefs, volume 6, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1981 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Energy efficient hardware acceleration of multimedia processing tools

The world of mobile devices is experiencing an ongoing trend of feature enhancement and generalpurpose multimedia platform convergence. This trend poses many grand challenges, the most pressing being their limited battery life as a consequence of delivering computationally demanding features. The envisaged mobile application features can be considered to be accelerated by a set of underpinning hardware blocks Based on the survey that this thesis presents on modem video compression standards and their associated enabling technologies, it is concluded that tight energy and throughput constraints can still be effectively tackled at algorithmic level in order to design re-usable optimised hardware acceleration cores. To prove these conclusions, the work m this thesis is focused on two of the basic enabling technologies that support mobile video applications, namely the Shape Adaptive Discrete Cosine Transform (SA-DCT) and its inverse, the SA-IDCT. The hardware architectures presented in this work have been designed with energy efficiency in mind. This goal is achieved by employing high level techniques such as redundant computation elimination, parallelism and low switching computation structures. Both architectures compare favourably against the relevant pnor art in the literature. The SA-DCT/IDCT technologies are instances of a more general computation - namely, both are Constant Matrix Multiplication (CMM) operations. Thus, this thesis also proposes an algorithm for the efficient hardware design of any general CMM-based enabling technology. The proposed algorithm leverages the effective solution search capability of genetic programming. A bonus feature of the proposed modelling approach is that it is further amenable to hardware acceleration. Another bonus feature is an early exit mechanism that achieves large search space reductions .Results show an improvement on state of the art algorithms with future potential for even greater savings