Utilization-based techniques for statically mapping heterogeneous applications onto the HiPer-D hetergeneous computing system

Includes bibliographical references (pages 16-18).This research investigates the problem of allocating a set of heterogeneous applications to a set of heterogeneous machines connected together by a high-speed network. The proposed resource allocation heuristics were implemented on the High Performance Distributed Computing Program's (HiPer-D) Naval Surface Warfare Center testbed. The goal of this study is to design static resource allocation heuristics that balance the utilization of the computation and network resources while ensuring very low failure rates. A failure occurs if no allocation is found that allows the system to meet its resource and quality of service constraints. The broader goal is to determine an initial resource allocation that maximizes the time before run-time re-allocation is required for managing an increased workload. This study proposes two heuristics that perform well with respect to the load-balancing and failure rates. These heuristics are, therefore, very desirable for HiPer-D like systems where low failure rates can be a critical requirement

Greedy Heuristics for Resource Allocation in Dynamic Distributed Real-Time Heterogeneous Computing Systems

Recently, with the widespread use of increasingly powerful commercial off-the-shelf (COTS) products, some real-time distributed system designers have started a shift from custom-made systems to COTS-based systems to get lower costs and more flexible systems. This research investigates the problem of allocating real-time applications to a set of COTS heterogeneous machines connected together by a COTS high-speed network. For the intended distributed real-time system, the work presented in this paper includes characterizing and modeling the applications and the hardware platform, identifying and quantifying the performance goal, and designing and developing heuristics for allocating the applications so as to optimize the performance goal. Each application has certain quality of service (QoS) constraints that must not be violated (e.g., constraints on the end-to-end latency and throughput). Unlike most of the related work in real-time systems, the focus of this work is on finding an initial static allocation of the applications onto the machines to maximize the allowable increase in workload until dynamic reallocation of resources is required to avoid a QoS violation. This paper presents and compares three greedy heuristics to solve the initial mapping problem

Utilization-Based Heuristics for Statically Mapping Real-Time Applications onto the HiPer-D Heterogeneous Computing System

Real-time applications continue to increase in importance as they are employed in various critical areas, such as command and control systems. These applications have traditionally required custom-made systems to execute them. Recently, with the widespread use of increasingly powerful commercial off-the-shelf (COTS) products, some real-time system designers have started a shift from custom development to COTS-based systems to achieve lower costs and more flexible systems. This research investigates the problem of allocating real-time applications to a set of COTS heterogeneous machines connected together by a COTS high-speed network. The heuristics were implemented on the High Performance Distributed Computing Program's (HiPer-D) Naval Surface Warfare Center (NSWC) testbed. At the specification of NSWC, the goal of this study is to design static resource allocation heuristics that balance the utilization of the computation and network resources in the HiPer-D system based on the system information provided. The broader goal is to maximize the time before dynamic reallocation is required for managing an increased workload at runtime