Efficient Utilization of Fine-Grained Parallelism using a microHeterogeneous Environment

The goal of this thesis is to propose a new computing paradigm, called micro- Heterogeneous computing or mHC, which incorporates PCI (or other high speed local system bus) based processing elements (vector processors, digital signal processors, etc) into a general purpose machine. In this manner the benefits of heterogeneous computing on scientific applications can be achieved while avoiding some of the lim itations. Overall performance is increased by exploiting fine-grained parallelism on the most efficient architecture available, while reducing the high communication over head and costs of traditional heterogeneous environments. Furthermore, mHC based machines can be combined into a cluster, allowing both the coarse-grained and fine grained parallelism to be fully exploited in order to achieve even greater levels of performance. An existing high performance computing API (GSL) was chosen as the interface to the system to allow for easy integration with applications that were previously developed using this API. The ensuing chapters will provide the motivation for this work, an overview of heterogenous computing, and the details pertaining to microHeterogeneous comput ing. The framework implemented to demonstrate a microHeterogeneous computing environment will be examined as well as the results. Finally, the future of micro Heterogeneous computing will be discussed

ORLease: Optimistically Replicated Lease Using Lease Version Vector For Higher Replica Consistency in Optimistic Replication Systems

There is a tradeoff between the availability and consistency properties of any distributed replication system. Optimistic replication favors high availability over strong consistency so that the replication system can support disconnected replicas as well as high network latency between replicas. Optimistic replication improves the availability of these systems by allowing data updates to be committed at their originating replicas first before they are asynchronously replicated out and committed later at the rest of the replicas. This leads the whole system to suffer from a relaxed data consistency. This is due to the lack of any locking mechanism to synchronize access to the replicated data resources in order to mutually exclude one another. When consistency is relaxed, there is a potential of reading from stale data as well as introducing data conflicts due to the concurrent data updates that might have been introduced at different replicas. These issues could be ameliorated if the optimistic replication system is aggressively propagating the data updates at times of good network connectivity between replicas. However, aggressive propagation for data updates does not scale well in write intensive environments and leads to communication overhead in order to keep all replicas in sync. In pursuance of a solution to mitigate the relaxed consistency drawback, a new technique has been developed that improves the consistency of optimistic replication systems without sacrificing its availability and with minimal communication overhead. This new methodology is based on applying the concurrency control technique of leasing in an optimistic way. The optimistic lease technique is built on top of a replication framework that prioritizes metadata replication over data replication. The framework treats the lease requests as replication metadata updates and replicates them aggressively in order to optimistically acquire leases on replicated data resources. The technique is demonstrating a best effort semi-locking semantics that improves the overall system consistency while avoiding any locking issues that could arise in optimistic replication systems