There is a current need for scheduling policies that can leverage the performance variability of resources on multiuser clusters. We develop one solution to this problem called stochastic scheduling that utilizes a distribution of application execution performance on the target resources to determine a performance-efficient schedule. In this paper, we define a stochastic scheduling policy based on time-balancing for data parallel applications whose execution behavior can be represented as a normal distribution. Using three distributed applications on two contended platforms, we demonstrate that a stochastic scheduling policy can achieve good and predictable performance for the application as evaluated by several performance measures.

this paper we show that different load balancing schemes are best for different applications under varying program and system parameters. Therefore, application-driven customized dynamic load balancing becomes essential for good performance. We present a hybrid compile-time and run-time modeling and decision process which selects (customizes) the best scheme, along with automatic generation of parallel code with calls to a run-time library for load balancing. 1997 Academic Press 1.

It is increasingly common for computer users to have access to several computers on a network, and hence tobe able to execute many of their tasks on any of several computers. The choice of which computers execute which tasks is commonly determined by users based on a knowledge of computer speeds for each task and the current load on each computer. A number of task scheduling systems have been developed that balance the load of the computers on the network, but such systems tend to minimize the idle time of the computers rather than minimize the idle time of the users. This paper focusesonthebene ts that can be achieved when the scheduling system considers both the computer availabilities and the performance of each task on each computer. The SmartNet resource scheduling system is described and compared to two di erent resource allocation strategies: load balancing and user directed assignment. Results are presented where theoperation of hundreds of di erent networks of computers running thousands of di erent mixes of tasks are simulated in a batch environment. These results indicate that, for the computer environments

We present a structural performance model that uses application profiles and component models to predict an application's performance on a set of distributed resources. We decompose application performance in accordance with the structure of the application: that is, into interacting component models that correspond to component tasks. Then, using the application profile and available information as guides, we select models for each component appropriately. As a proof of concept, we have implemented this approach for two distributed applications, a master-slave genetic algorithm code and a red-black stencil successive over-relaxation code. Our predictions are within 10% of actual time. Context Clusters of distributed machines have become a common platform for high performance applications, but remain a challenging environment in which to achieve good performance. One reason for this is the difficulty of predicting an application's execution time in this variable setting, where only mi...

This paper presents a simulation-based performance prediction framework for large scale data-intensive applications on large scale machines. Our framework consists of two components: application emulators and a suite of simulators. Application emulators provide a parameterized model of data access and computation patterns of the applications and enable changing of critical application components #input data partitioning, data declustering, processing structure, etc.# easily and #exibly. Our suite of simulators model the I#O and communication subsystems with good accuracy and execute quickly on a high-performance workstation to allow performance prediction of large scale parallel machine con#gurations. The key to e#cient simulation of very large scale con#gurations is a technique called loosely-coupled simulation where the processing structure of the application is embedded in the simulator, while preserving data dependencies and data distributions. Weevaluate our performance ...

The requirements of grand challenge problems and the deployment of gigabit networks makes the network computing framework an attractive and cost effective computing environment with which to interconnect geographically distributed processing and storage resources. Our project, Virtual Distributed Computing Environment (VDCE), provides a problem-solving environment for high-performance distributed computing over wide area networks. VDCE delivers well-defined library functions that relieve end-users of tedious task implementations and also support reusability. In this paper we present the conceptual design of VDCE software architecture, which is defined in three modules: a) the Application Editor, a user-friendly application development environment that generates the Application Flow Graph (AFG) of an application; b) the Application Scheduler, which provides an efficient task-toresource mapping of AFG; and c) the VDCE Runtime System, which is responsible for running and managing applicat...

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We address the problem of performance prediction for parallel programs executed on clusters of heterogeneous workstations on which resource contention is present. We develop a methodology for the construction of performance models whose analysis allows the estimation of the execution time of these programs. We use Timed Petri Nets to represent the behavior of parallel programs, and a contention model based on queueing theory to quantify the effects of resource contention on the execution time of the application processes. Our methodology is demonstrated through the construction of the model of an example program, which is also used to validate the predictions against measured execution times obtained by executing the program on two different clusters of workstations. 1 Introduction Clusters of workstations are increasingly being used as costeffective parallel computing platforms, but their effective exploitation requires consideration of many of the research problems already addresse...

this paper we present the Virtual Distributed Computing Environment (VDCE), a metacomputing environment currently being developed at Syracuse University. VDCE provides an efficient web-based approach for developing, evaluating and visualizing large-scale distributed applications that are based on predefined task libraries on diverse platforms. The VDCE task libraries relieve end-users of tedious task implementations and also support reusability. The VDCE software architecture is described in terms of three modules: a) the Application Editor, a user-friendly application development environment that generates the Application Flow Graph (AFG) of an application; b) the Application Scheduler, which provides an efficient task-to-resource mapping of AFG; and c) the VDCE Runtime System, which is responsible for running and managing application execution and for monitoring the VDCE resources. We present experimental results of an application execution on the VDCE prototype for evaluating the performance of different machine and network configurations. We also show how VDCE can be used as a problem-solving environment on which large-scale, network-centric applications can be developed by a novice programmer rather than by an expert in low-level details of parallel programming languages.

This thesis examines two largely unrelated problems in applied algorithmics, motivated by the search for efficient geometric algorithms. In the first part of the thesis, we consider the problem of finding efficient parallel algorithms for heterogeneous parallel computers, i.e., parallel computers in which different processors have different computational potential. To this end, we define a formal computational model for heterogeneous systems and develop algorithms for commonly used communication operations. The result is that many existing parallel algorithms which use these communication operations can be adapted to our model with little or no modifications. In the second part of the thesis we consider the problem of geometric models which allow for varying levels of detail. To this end, we extend the progressive mesh representation introduced by Hoppe. The main technical contribution of this part is an efficient scheme for refining only selected regions of a progressive mesh. Using ...