Heterogeneous PC Cluster Research Articles

Performance-based dynamic loop scheduling in heterogeneous computing environments

With the rapid advance of computing technologies, it becomes more and more common to construct high-performance computing environments with heterogeneous commodity computers. Previous loop scheduling schemes were not designed for this kind of environments. Therefore, better loop scheduling schemes are needed to further increase the performance of the emerging heterogeneous PC cluster environments. In this paper, we propose a new heuristic for the performance-based approach to partition loop iterations according to the performance weighting of cluster/grid nodes. In particular, a new parameter is proposed to consider HPCC benchmark results as part of performance estimation. A heterogeneous cluster and grid were built to verify the proposed approach, and three kinds of application program were implemented for execution on cluster testbed. Experimental results show that the proposed approach performs better than the previous schemes on heterogeneous computing environments.

An Efficient Parallel Solution Framework for the Linear Solution of Large Systems on PC Clusters

In this paper, a parallel solution framework for the linear static analysis of large structures on PC clusters is presented. The framework consists of two main steps: data preparation and parallel solution. The parallel solution is performed by a substructure based method with direct solvers. The aim of the data preparation step is to create the best possible substructures so that the parallel solution time is minimized. An actual structural model was solved utilizing both homogeneous and heterogeneous PC clusters to illustrate the performance and applicability of the presented framework.

Dynamic partitioning of loop iterations on heterogeneous PC clusters

Loop partitioning on parallel and distributed systems has been a critical problem. Furthermore, it becomes more difficult to deal with on the emerging heterogeneous PC cluster environments. In the past, some loop self-scheduling schemes have been proposed to be applicable to heterogeneous cluster environments. In this paper, we propose a performance-based approach, which partitions loop iterations according to the performance ratio of cluster nodes. To verify the proposed approach, a heterogeneous cluster is built, and three types of application programs are implemented to be executed in this testbed. Experimental results show that the proposed approach performs better than traditional schemes.

An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments

Approaches for dealing with scheduling and load-balancing in PC-based cluster systems are famous and well known. In such environments, Self-Scheduling Schemes are suitable for parallel loops with independent iterations. However, while schemes such as FSS, GSS, and TSS fit most computer systems, they cannot provide good load-balancing. Chao-Tung Yang and Shun-Chi Chang proposed a parallel loop scheduling scheme for heterogeneous PC cluster systems in Yang and Chang [13]. Though the proposed scheme allows users to choose parameters before execution initialization, weaknesses in it motivated us to develop further improvements. For instance, using fixed and monotonous parameters can easily lead to invalid scheduling due to use of previously input information. Thus, in this paper we propose a new scheme that fits most widely available computer systems and allows the scheduling parameter to be adjusted dynamically in order to provide higher overall performance.

A Parallel Loop Self-Scheduling on Extremely Heterogeneous PC Clusters

Cluster computers are a viable and less expensive alternative to symmetric multiprocessor systems. However, a serious difficulty in concurrent programming of a cluster computer system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers Self-scheduling schemes suitable for parallel loops with independent iterations on heterogeneous computer clusters have been designed in the past These schemes, such as FSS, GSS and TSS, can achieve load balancing in SMP, even in a moderate heterogeneous environment, but are not suitable in extremely heterogeneous environments. In this paper, we propose a heuristic approach to solve parallel loop scheduling problems on an extremely heterogeneous PC cluster environment.

On Exploiting Heterogeneity for Cluster Based Parallel Multithreading Using Task Duplication

Triggered by the ever increasing advancements in processor and networking technology, a cluster of PCs connected by a high-speed network has become a viable and cost-effective platform for the execution of computation intensive parallel multithreaded applications. However, there are two research issues to be tackled in the scheduling problem for PC cluster computing: (1) how to reduce the communication overhead of executing a multithreaded application on the cluster; (2) how to exploit the heterogeneity, which is unavoidable in an evolving PC cluster, for the application. In this paper, we propose to use a duplication based approach in scheduling tasks/threads to a heterogeneous cluster of PCs. In duplication based scheduling, critical tasks are redundantly scheduled to more than one machine, in order to reduce the number of inter-task communication operations. The start times of the succeeding tasks are also reduced. The task duplication process is guided given the system heterogeneity in that the critical tasks are scheduled or replicated in faster machines. The algorithm has been implemented in our experimental application parallelization system for generating multithreaded parallel code executable on a cluster of Pentium PCs. Our experiments, using three numerical applications and one protocol processing kernel (multithreading per request), have indicated that heterogeneity of PC cluster is indeed useful for optimizing the execution of parallel multithreaded programs.

Application of Parallel Virtual Machine Framework to the Strong Prime Problem

This paper use the well-discussed PVM (Parallel Virtual Machine) software with several personal computers, and adopt the widespread Microsoft Windows '98 operating system as our operation platform to construct a heterogeneous PCs cluster. By engaging the related researches of PC cluster system and cluster computing theory, we apply our heterogeneous PC cluster computing system to generate more secure parameters for some public key cryptosystems such as RSA. Copes with each parameter's related mathematic theory's restriction, enormous computation power is needed to get better computation performance in generating these parameters. In this paper, we contribute heterogeneous PCs combined with the PVM software to cryptosystem parameters, which is conformed to today's safety specification and requirement. We practically generate these data to prove that computer cluster can effectively accumulate enormous computation power, and then demonstrate the cluster computation application in finding strong primes which are needed in some public key cryptosystems.

Load balancing for heterogeneous clusters of PCs

With commercial supercomputers and homogeneous clusters of PCs, static load balancing is accomplished by assigning equal tasks to each processor. With heterogeneous clusters, the system designers have the option of quickly adding newer hardware that is more powerful than the existing hardware. When this is done, the assignment of equal tasks to each processor results in suboptimal performance. This research addresses techniques by which the size of the task assigned to a processor is a suitable match. Thus, the more powerful processors do more work and the less powerful processors perform less work. We find that when the range of processing power is narrow, some benefit can be achieved with asymmetric load balancing. When the range of processing power is broad, dramatic improvements in performance are realized — our experiments have shown up to 92% improvement when asymmetrically load balancing a modified version of the computationally intensive NAS Parallel Benchmarks’ LU application on a heterogeneous cluster of Linux-powered PCs.

Synchronization in portable device drivers

We present an overview of the synchronization mechanisms offered to device drivers by different operating systems and develop a foundation for writing portable device drivers by unifying these mechanisms. Our foundation has been used to implement an efficient portable cluster adapter driver for three different operating systems as part of the runtime system for a heterogeneous PC cluster. We show how our portable synchronization mechanisms map to the native synchronization mechanisms of these three operating systems.

Synchronization in portable device drivers

We present an overview of the synchronization mechanisms offered to device drivers by different operating systems and develop a foundation for writing portable device drivers by unifying these mechanisms. Our foundation has been used to implement an efficient portable cluster adapter driver for three different operating systems as part of the runtime system for a heterogeneous PC cluster. We show how our portable synchronization mechanisms map to the native synchronization mechanisms of these three operating systems.