44 research outputs found

    Efficient processor management strategies for multicomputer systems

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    Multicomputers are cost-effective alternatives to the conventional supercomputers. Contemporary processor management schemes tend to underutilize the processors and leave many of the processors in the system idle while jobs are waiting for execution;Instead of designing faster processors or interconnection networks, a substantial performance improvement can be obtained by implementing better processor management strategies. This dissertation studies the performance issues related to the processor management schemes and proposes several ways to enhance the multicomputer systems by means of processor management. The proposed schemes incorporate the concepts of size-reduction, non-contiguous allocation, as well as job migration. Job scheduling using a bypass-queue is also studied. All the proposed schemes are proven effective in improving the system performance via extensive simulations. Each proposed scheme has different implementation cost and constraints. In order to take advantage of these schemes, judicious selection of system parameters is important and is discussed

    An efficient processor allocation strategy that maintains a high degree of contiguity among processors in 2D mesh connected multicomputers

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    Two strategies are used for the allocation of jobs to processors connected by mesh topologies: contiguous allocation and non-contiguous allocation. In non-contiguous allocation, a job request can be split into smaller parts that are allocated to non-adjacent free sub-meshes rather than always waiting until a single sub-mesh of the requested size and shape is available. Lifting the contiguity condition is expected to reduce processor fragmentation and increase system utilization. However, the distances traversed by messages can be long, and as a result the communication overhead, especially contention, is increased. The extra communication overhead depends on how the allocation request is partitioned and assigned to free sub-meshes. This paper presents a new Non-contiguous allocation algorithm, referred to as Greedy-Available-Busy-List (GABL for short), which can decrease the communication overhead among processors allocated to a given job. The simulation results show that the new strategy can reduce the communication overhead and substantially improve performance in terms of parameters such as job turnaround time and system utilization. Moreover, the results reveal that the Shortest-Service-Demand-First (SSD) scheduling strategy is much better than the First-Come-First-Served (FCFS) scheduling strategy

    An improved generalization of mesh-connected computers with multiple buses

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    ©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Mesh-connected computers (MCCs) are a class of important parallel architectures due to their simple and regular interconnections. However, their performances are restricted by their large diameters. Various augmenting mechanisms have been proposed to enhance the communication efficiency of MCCs. One major approach is to add nonconfigurable buses for improved broadcasting. A typical example is the mesh-connected computer with multiple buses (MMB). We propose a new class of generalized MMBs, the improved generalized MMBs (IMMBs). We compare IMMBs with MMBs and a class of previously proposed generalized MMBs (GMMBs). We show the power of IMMBs by considering semigroup and prefix computations. Specifically, as our main result we show that for any constant 0<&epsiv;<1, one can construct an N½×N½ square IMMB using which semigroup and prefix computations on N operands can be carried out in O(N&epsiv;) time, while maintaining O(1) broadcasting time. Compared with the previous best complexities O(N&frac18;) and O(N&frac116;) achieved on a rectangular MMB and GMMB, respectively, for the same computations, our results show that IMMBs are more powerful than MMBs and GMMBsYi Pen; Zheng, S.Q.; Keqin Li; Hong She

    Processor allocator for chip multiprocessors

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    Chip MultiProcessor (CMP) architectures consisting of many cores connected through Network-on-Chip (NoC) are becoming main computing platforms for research and computer centers, and in the future for commercial solutions. In order to effectively use CMPs, operating system is an important factor and it should support a multiuser environment in which many parallel jobs are executed simultaneously. It is done by the processor management system of the operating system, which consists of two components: Job Scheduler (JS) and Processor Allocator (PA). The JS is responsible for job scheduling that deals with selection of the next job to be executed, while the task of the PA is processor allocation that selects a set of processors for the job selected by the JS. In this thesis, the PA architecture for the NoC-based CMP is explored. The idea of the PA hardware implementation and its integration on one die together with processing elements of CMP is presented. Such an approach requires the PA to be fast as well as area and energy efficient, because it is only a small component of the CMP. The architecture of hardware version of a PA is presented. The main factor of the structure is a type of processor allocation algorithm, employed inside. Thus, all important allocation techniques are intensively investigated and new schemes are proposed. All of them are compared using experimentation system. The PA driven by the described allocation techniques is synthesized on FPGA and crucial energy and area consumption together with performance parameters are extracted. The proposed CMP uses NoC as interconnection architecture. Therefore, all main NoC structures are studied and tested. Most important parameters such as topology, flow control and routing algorithms are presented and discussed. For the proposed NoC structures, an energy model is proposed and described. Finally, the synthesized PAs and NoCs are evaluated in a simulation system, where NoC-based CMP is created. The experimental environment took into consideration energy and traffic balance characteristics. As a result, the most efficient PA and NoC for CMP are presented

    Hardware Implementation Of Processor Allocator For Mesh Connected Chip Multiprocessors

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    The advancements in the semiconductor process technology and the current demand for highly parallel computing has led to the advent of Chip Multiprocessors (CMPs). CMP is the integration of two or more independent processor cores, which can read and execute program instructions, on to a single integrated circuit die. CMPs are the main computing platforms for research and development in parallel and high performance computing environments. They offer minimum inter-core communication latencies as the processor cores are present on a single chip. The Operating System (OS) plays a key role in using a CMP effectively. The OS should support a multi-user environment in which the jobs are executed in parallel on different cores. This is handled by the processor management system of the OS. The Processor Management System consists of Job Scheduler (JS) and Processor Allocator (PA). The JS aligns the jobs in a queue in an order which is determined by the scheduling policy employed and thus specifying the job that is to be executed next. The PA deals with the selection of appropriate set of processors to execute the job scheduled by the job scheduler. Efficient design of a PA is crucial if one is to harness the full computational power of a CMP in large parallel computing systems. This thesis deals with the processor allocation part of the processor management system. The motive of this thesis is the hardware implementation of a PA for a mesh-connected CMP. The PA is implemented and a synthesis report is presented which shows the amount of logic utilized. Many contiguous and non-contiguous allocation strategies have been proposed for mesh networks in the recent years. The Improvised First Fit algorithm is used to select the appropriate set of processors for executing an incoming job in this hardware implementation. This algorithm is a contiguous allocation algorithm and has complete sub-mesh recognition ability and uses a bit-map approach. The JS is assumed to be employing a First Come First Serve (FCFS) policy to schedule the jobs. This thesis also acts as the basis for the hardware implementation of PA that uses other allocation algorithms in different topologies

    Redundancy management for efficient fault recovery in NASA's distributed computing system

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    The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance

    Design and Analysis of Optical Interconnection Networks for Parallel Computation.

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    In this doctoral research, we propose several novel protocols and topologies for the interconnection of massively parallel processors. These new technologies achieve considerable improvements in system performance and structure simplicity. Currently, synchronous protocols are used in optical TDM buses. The major disadvantage of a synchronous protocol is the waste of packet slots. To offset this inherent drawback of synchronous TDM, a pipelined asynchronous TDM optical bus is proposed. The simulation results show that the performance of the proposed bus is significantly better than that of known pipelined synchronous TDM optical buses. Practically, the computation power of the plain TDM protocol is limited. Various extensions must be added to the system. In this research, a new pipelined optical TDM bus for implementing a linear array parallel computer architecture is proposed. The switches on the receiving segment of the bus can be dynamically controlled, which make the system highly reconfigurable. To build large and scalable systems, we need new network architectures that are suitable for optical interconnections. A new kind of reconfigurable bus called segmented bus is introduced to achieve reduced structure simplicity and increased concurrency. We show that parallel architectures based on segmented buses are versatile by showing that it can simulate parallel communication patterns supported by a wide variety of networks with small slowdown factors. New kinds of interconnection networks, the hypernetworks, have been proposed recently. Compared with point-to-point networks, they allow for increased resource-sharing and communication bandwidth utilization, and they are especially suitable for optical interconnects. One way to derive a hypernetwork is by finding the dual of a point-to-point network. Hypercube Q\sb{n}, where n is the dimension, is a very popular point-to-point network. It is interesting to construct hypernetworks from the dual Q\sbsp{n}{*} of hypercube of Q\sb{n}. In this research, the properties of Q\sbsp{n}{*} are investigated and a set of fundamental data communication algorithms for Q\sbsp{n}{*} are presented. The results indicate that the Q\sbsp{n}{*} hypernetwork is a useful and promising interconnection structure for high-performance parallel and distributed computing systems

    On the Potential of NoC Virtualization for Multicore Chips

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    Effective Large Scale Computing Software for Parallel Mesh Generation

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    Scientists commonly turn to supercomputers or Clusters of Workstations with hundreds (even thousands) of nodes to generate meshes for large-scale simulations. Parallel mesh generation software is then used to decompose the original mesh generation problem into smaller sub-problems that can be solved (meshed) in parallel. The size of the final mesh is limited by the amount of aggregate memory of the parallel machine. Also, requesting many compute nodes on a shared computing resource may result in a long waiting, far surpassing the time it takes to solve the problem.;These two problems (i.e., insufficient memory when computing on a small number of nodes, and long waiting times when using many nodes from a shared computing resource) can be addressed by using out-of-core algorithms. These are algorithms that keep most of the dataset out-of-core (i.e., outside of memory, on disk) and load only a portion in-core (i.e., into memory) at a time.;We explored two approaches to out-of-core computing. First, we presented a traditional approach, which is to modify the existing in-core algorithms to enable out-of-core computing. While we achieved good performance with this approach the task is complex and labor intensive. An alternative approach, we presented a runtime system designed to support out-of-core applications. It requires little modification of the existing in-core application code and still produces acceptable results. Evaluation of the runtime system showed little performance degradation while simplifying and shortening the development cycle of out-of-core applications. The overhead from using the runtime system for small problem sizes is between 12% and 41% while the overlap of computation, communication and disk I/O is above 50% and as high as 61% for large problems.;The main contribution of our work is the ability to utilize computing resources more effectively. The user has a choice of either solving larger problems, that otherwise would not be possible, or solving problems of the same size but using fewer computing nodes, thus reducing the waiting time on shared clusters and supercomputers. We demonstrated that the latter could potentially lead to substantially shorter wall-clock time
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