Lic.-avh. Västerås : Mälardalens högskola, 2008. / S. 75-79: Bibliografi.

Thesis (Ph. D.)--Florida State University, 2006. / Advisor: Xin Yuan, Florida State University, College of Arts and Sciences, Dept. of Computer Science. Title and description from dissertation home page (viewed Sept. 19, 2006). Document formatted into pages; contains xiii, 162 pages. Includes bibliographical references.

This thesis presents and evaluates a new parallel algorithm that computes all single cosets in the double coset M₂₄ P M₂₄, where P is a permutation on n points of a certain cycle structure, and M₂₄ is the Mathieu group related to a Steiner system S(5, 8, 24) as its automorphism group. The purpose of this work is not to replace the existing algorithms, but rather to explore a possibility to extend calculations of single cosets beyond the limits encountered when using currently available methods.

No description available.

In many languages, the programmer is provided the capability of communicating through the use of function calls with other, separate, independent processes. This capability can be as simple as a service request made to the operating system or as advanced as Tuple Space operations specific to a Linda programming system. The problem with such calls, however, is that they block while waiting for data or information to be returned. This synchronous nature and lack of concurrency can be avoided by initiating a non-blocking request for data earlier in the code and retrieving the returned data later when it is needed. To facilitate a better understanding of how this type of concurrency can be exploited, we introduce an instructional footprint model and application framework that formally describes instructional decomposition and code motion activities. To demonstrate the effectiveness of such an approach, we apply instructional footprinting to programs using the Linda coordination language. <i>Linda Primitive Transposition</i> (LPT) and <i>Instruction Piggybacking</i> are discussed as techniques to increase the size of instructional footprints, and thereby improve the performance of Linda programs. We also present the concept of <i>Lexical Proximity</i> to demonstrate how the overlapping of footprints contributes to the speedup of Linda programs. / Ph. D.

The purpose of the thesis is to develop a parallel implementation of the General Block Min Max Criterion (GBMM). This thesis deals with two kinds of parallel overheads: Redundant Calculations Parallel Overhead (RCPO) and Communication Parallel Overhead (CPO).

Within the last decade multi-core processors have become increasingly commonplace with the power and performance demands of modern real-world programs acting to accelerate this trend. The rapid advancements in designing and adoption of such architectures mean that there is a serious need for programming models that allow the development of correct parallel programs that execute efficiently on these processors. A principle problem in this regard is that of efficiently synchronizing concurrent accesses to shared memory. Traditional solutions to this problem are either inefficient but provide programmability (coarse-grained locks) or are efficient but are not composable and very hard to program and verify (fine-grained locks). Optimistic Transactional Memory systems provide many of the composability and programmabillity advantages of coarse-grained locks and good theoretical scaling but several studies have found that their performance in practice for many programs remains quite poor primarily because of the high overheads of providing safe optimism. Moreover current transactional memory models remain rigid - they are not suited for expressing some of the complex thread interactions that are prevalent in modern parallel programs. Moreover, the synchronization achieved by these transactional memory systems is at the physical or memory level. This thesis advocates a position that memory synchronization problem for threads should be modeled and solved in terms of synchronization of underlying program values which have semantics associated with them. It presents optimistic synchronization techniques that address the semantic synchronization requirements of a parallel program instead. These techniques include methods to 1) enable optimistic transactions to recover from expensive sharing conflicts without discarding all the work made possible by the optimism 2) enable a hybrid pessimistic-optimistic form of concurrency control that lowers overheads 3) make synchronization value-aware and semantics-aware 4) enable finer grained consistency rules (than allowed by traditional optimistic TM models) therefore avoiding conflicts that do not enforce any semantic property required by the program. In addition to improving the expressibility of specific synchronization idioms all these techniques are also effective in improving parallel performance. This thesis formulates these techniques in terms of their purpose, the extensions to the language, the compiler as well as to the concurrency control runtime necessary to implement them. It also briefly presents an experimental evaluation of each of them on a variety of modern parallel workloads. These experiments show that these techniques significantly improve parallel performance and scalability over programs using state-of-the-art optimistic synchronization methods.

Thesis (M.S.)--Mississippi State University. Department of Computer Science. / Title from title screen. Includes bibliographical references.

Thesis (M.S.)--Mississippi State University. Department of Computer Science and Engineering. / Title from title screen. Includes bibliographical references.

Transactional memory systems are expected to enable parallel programming at lower programming complexity, while delivering improved performance over traditional lock-based systems. Nonetheless, there are certain situations where transactional memory systems could actually perform worse. Transactional memory systems can outperform locks only when the executing workloads contain sufficient parallelism. When the workload lacks inherent parallelism, launching excessive transactions can adversely degrade performance. These situations will actually become dominant in future workloads when large-scale transactions are frequently executed. In this thesis, we propose a new paradigm called adaptive transaction scheduling to address this issue. Based on the parallelism feedback from applications, our adaptive transaction scheduler dynamically dispatches and controls the number of concurrently executing transactions. In our case study, we show that our low-cost mechanism not only guarantees that hardware transactional memory systems perform no worse than a single global lock, but also significantly improves performance for both hardware and software transactional memory systems.