A Cloud Powered Relaxed Heterogeneous Distributed Shared Memory System

Distributed systems allow the existence of impressive pieces of software, but usually impose strict restrictions on the implementation language and model. We propose a distribution system model that enables the incorporation of any hardware device connected to the internet as its nodes, and places no restriction on the execution engine, allowing the transparent incorporation of any existing codebase into a Distributed Shared Memory.XIX Workshop Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

A Cloud Powered Relaxed Heterogeneous Distributed Shared Memory System

Distributed systems allow the existence of impressive pieces of software, but usually impose strict restrictions on the implementation language and model. We propose a distribution system model that enables the incorporation of any hardware device connected to the internet as its nodes, and places no restriction on the execution engine, allowing the transparent incorporation of any existing codebase into a Distributed Shared Memory.XIX Workshop Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

Parallel performance prediction for numerical codes in a multi-cluster environment

We propose a model for describing and predicting the performance of parallel numerical software on distributed memory architectures within a multi-cluster environment. The goal of the model is to allow reliable predictions to be made as to the execution time of a given code on a large number of processors of a given parallel system, and on a combination of systems, by only benchmarking the code on small numbers of processors. Thishas potential applications for the scheduling of jobs in a Grid computing environment where informed decisions about which resources to use in order to maximize the performance and/or minimize the cost of a job will be valuable. The methodology is built and tested for a particular class of numerical code, based upon the multilevel solution of discretized partial differential equations, and despite its simplicity it is demonstrated to be extremely accurate and robust with respect to both the processor and communications architectures considered. Furthermore,results are also presented which demonstrate that excellent predictions may also be obtained for numerical algorithms that are more general than the pure multigrid solver used to motivate the methodology. These are based upon the use of a practical parallel engineering code that is briefly described. The potential significance of this work is illustrated via two scenarios which consider a Grid user who wishes to use the available resources either (i) to obtain a particular result as quickly as possible, or (ii) to obtain results to different levels of accuracy. Index Terms—Parallel Distributed Algorithms; Grid Computing; Cluster Computing; Performance Evaluation and Prediction; Meta-Scheduling

A Cloud Powered Relaxed Heterogeneous Distributed Shared Memory System

Distributed systems allow the existence of impressive pieces of software, but usually impose strict restrictions on the implementation language and model. We propose a distribution system model that enables the incorporation of any hardware device connected to the internet as its nodes, and places no restriction on the execution engine, allowing the transparent incorporation of any existing codebase into a Distributed Shared Memory.XIX Workshop Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI