An Algorithm for Dynamic Load Balancing of Synchronous Monte Carlo Simulations on Multiprocessor Systems

We describe an algorithm for dynamic load balancing of geometrically parallelized synchronous Monte Carlo simulations of physical models. This algorithm is designed for a (heterogeneous) multiprocessor system of the MIMD type with distributed memory. The algorithm is based on a dynamic partitioning of the domain of the algorithm, taking into account the actual processor resources of the various processors of the multiprocessor system.Comment: 12 pages, uuencoded figures included, 75.93.0

Designing a scalable dynamic load -balancing algorithm for pipelined single program multiple data applications on a non-dedicated heterogeneous network of workstations

Dynamic load balancing strategies have been shown to be the most critical part of an efficient implementation of various applications on large distributed computing systems. The need for dynamic load balancing strategies increases when the underlying hardware is a non-dedicated heterogeneous network of workstations (HNOW). This research focuses on the single program multiple data (SPMD) programming model as it has been extensively used in parallel programming for its simplicity and scalability in terms of computational power and memory size.;This dissertation formally defines and addresses the problem of designing a scalable dynamic load-balancing algorithm for pipelined SPMD applications on non-dedicated HNOW. During this process, the HNOW parameters, SPMD application characteristics, and load-balancing performance parameters are identified.;The dissertation presents a taxonomy that categorizes general load balancing algorithms and a methodology that facilitates creating new algorithms that can harness the HNOW computing power and still preserve the scalability of the SPMD application.;The dissertation devises a new algorithm, DLAH (Dynamic Load-balancing Algorithm for HNOW). DLAH is based on a modified diffusion technique, which incorporates the HNOW parameters. Analytical performance bound for the worst-case scenario of the diffusion technique has been derived.;The dissertation develops and utilizes an HNOW simulation model to conduct extensive simulations. These simulations were used to validate DLAH and compare its performance to related dynamic algorithms. The simulations results show that DLAH algorithm is scalable and performs well for both homogeneous and heterogeneous networks. Detailed sensitivity analysis was conducted to study the effects of key parameters on performance

Efficient Load Balancing Algorithm in Long Term Evolution (LTE) Heterogeneous Network Based on Dynamic Cell Range Expansion Bias

The traditional scheme for load balancing in a homogeneous Long Term Evolution (LTE) Network where User Equipment (UEs) associate to a node with the strongest received signal strength is not practical for LTE Heterogeneous Network (LTE HetNet) due to power disparity between the nodes. Therefore, dynamic Cell Range Expansion (CRE) based load-balancing schemes were employed by several scholars to address the challenges in the LTE HetNet. However, the fairness index in achieving the desired average user throughput and UE offloading effect is relatively low. In this work, an efficient load-balancing algorithm for LTE HetNet based on dynamic Cell Range Expansion (CRE) was developed to improve the fairness of the network for the desired throughput and UE offloading effect. The simulation results achieve a throughput gain improvement of up to 11%, while the fairness index improves by 6% compared to the existing algorithm. Further, the UEs offloading effect shows a significant improvement of 3% relative to the existing algorithm. Keywords: Fairness Index; Cell Range Expansion; Load Balancing; LTE Heterogeneous Network; Throughpu

Load Balancing and Job Migration Algorithms for Autonomic Grid Environment

Resource management and load balancing are the main areas of concern in a distributed, heterogeneous and dynamic environment like Grid. Load balancing may further cause Job migration or in some cases resubmission of Job. In this paper a number of job migration algorithms have been surveyed and studied which have resulted because of the Load balancing problem. A comparative analysis of these algorithms has also been presented which summarizes the utility and applicability of different algorithms in different environment and circumstances

Dynamic load balancing strategies in heterogeneous distributed system

Distributed heterogeneous computing is being widely applied to a variety of large size computational problems. This computational environments are consists of multiple het- erogeneous computing modules, these modules interact with each other to solve the prob-lem. Dynamic load balancing in distributed computing system is desirable because it is an important key to establish dependability in a Heterogeneous Distributed Computing Systems (HDCS). Load balancing problem is an optimization problem with exponential solution space. The complexity of dynamic load balancing increases with the size of a HDCS and becomes difficult to solve effectively. The solution to this intractable problem is discussed under different algorithm paradigm.The load submitted to the a HDCS is assumed to be in the form of tasks. Dynamic allocation of n independent tasks to m computing nodes in heterogeneous distributed computing system can be possible through centralized or decentralized control. In central-ized approach,we have formulated load balancing problem considering task and machine heterogeneity as a linear programming problem to minimize the time by which all task completes the execution in makespan.The load balancing problem in HDCS aims to maintain a balanced allocation of tasks while using the computational resources. The system state changes with time on arrival of tasks from the users. Therefore,heterogeneous distributed system is modeled as an M/M/m queue. The task model is represented either as a consistent or an inconsistent expected time to compute (ETC) matrix. A batch mode heuristic has been used to de-sign dynamic load balancing algorithms for heterogeneous distributed computing systems with four different type of machine heterogeneity. A number of experiments have been conducted to study the performance of load balancing algorithms with three different ar-rival rate for the task. A better performance of the algorithms is observed with increasing of heterogeneity in the HDCS.A new codification scheme suitable to simulated annealing and genetic algorithm has been introduced to design dynamic load balancing algorithms for HDCS. These stochastic iterative load balancing algorithms uses sliding window techniques to select a batch of tasks, and allocate them to the computing nodes in the HDCS. The proposed dynamic genetic algorithm based load balancer has been found to be effective, especially in the case of a large number of tasks

Dynamic Load Balancing By Scheduling In Computational Grid System

Grid computing systems are distributed systems that involve coordinate and involvement of heterogeneous resources with various characteristics where user jobs can be executed on either local or remote computer. These heterogeneous computing resources are used to run highly complex programs that require very high processing power and huge volume of input data. Recently the biggest issue in distributed system is to design of an appropriate and efficient dynamic load balancing algorithm that upgrade the overall performance of the distributed systems. In this research paper, we proposed a scheduling algorithm that manages the resources to improve the utilization of resource and minimize the job response time in computational grid system. So that no any resources will be heavily, low loaded or in some case will be in idle. Keywords— Grid computation, Dynamic Load balancing, Schedule DLB, Job Scheduling

Dynamic load balancing in parallel processing on non-homogeneous clusters

This paper analyzes the dynamic and static balancing of non-homogenous cluster architectures, simultaneously analyzing the theoretical parallel Speedup as well as the Speedup experimentally obtained. Three interconnected clusters have been used in which the machines within each cluster have homogeneous processors although different among clusters. Thus, the set can be seen as a 25-processor heterogeneous cluster or as a multi-cluster scheme with subsets of homogeneous processors. A classical application (Parallel N-Queens) with a parallel solution algorithm, where processing predominates upon communication, has been chosen so as to go deep in the load balancing aspects (dynamic or static) without distortion of results caused by communication overhead. At the same time, three forms of load distribution in the processors (Direct Static, Predictive Static and Dynamic by Demand) have been studied, analyzing in each case parallel Speedup and load unbalancing regarding problem size and the processors used.Facultad de Informátic

Coarray-based Load Balancing on Heterogeneous and Many-Core Architectures

In order to reach challenging performance goals, computer architecture is expected to change significantly in the near future. Heterogeneous chips, equipped with different types of cores and memory, will force application developers to deal with irregular communication patterns, high levels of parallelism, and unexpected behavior. Load balancing among the heterogeneous compute units will be a critical task in order to achieve an effective usage of the computational power provided by such new architectures. In this highly dynamic scenario, Partitioned Global Address Space (PGAS) languages, like Coarray Fortran, appear a promising alternative to standard MPI programming that uses two-sided communications, in particular because of PGAS one-sided semantic and ease of programmability. In this paper, we show how Coarray Fortran can be used for implementing dynamic load balancing algorithms on an exascale compute node and how these algorithms can produce performance benefits for an Asian option pricing problem, running in symmetric mode on Intel Xeon Phi Knights Corner and Knights Landing architectures