Research Of Software Low-power Optimization In Large-scale Parallel Computing System

Power consumption has become one of the most important constraints forperformance enhancement of large-scale parallel computing system. Too high powerand energy consumption has many negative effects on system running, which includeincreasing system failure frequency, reducing system reliability, increasing running costand so on. Therefore, studying power optimization of large-scale parallel computingsystem has important practical significance.Large-scale parallel computing system power optimization has been extended intoeach hiberarchy of system design and implementation, including circuit design, logicdesign, architecture, system software and applications. Dynamic voltage scale (DVS)and shutting down technology of hardware device provide implementation basis forsoftware power optimization. Software-level low power optimization has manyadvantages, such as hardware-platform independence, more flexibility, goodtransplantability and so on. Computing system and communication system compose thecrucial components of large-scale parallel computing system so that they are the focusof power optimization. From the viewpoint of low-power optimization softwaretechnology research in large-scale parallel computing system, this thesis studies loopscheduling based energy optimization of compute nodes, energy optimization ofinterconnection network based on network topology partition.The energy optimization of compute nodes is an important part of poweroptimization of large-scale parallel computing system. This thesis studies the OpenMPloop scheduling based energy optimization of compute nodes. Through combining DVSand scheduling algorithm, the thesis proposes two kinds of power optimizationalgorithms: performance-constrained energy optimization and energy-constrainedperformance optimization. Performance-constrained energy optimization improves theblock static scheduling algorithm and then propose Energy Saving Optimal StaticScheduling (EOSS) algorithm. The Improved Energy Optimal Static Scheduling(IEOSS) is then proposed which considers the impact of cache misses on the latency ofmemory access. Energy-constrained performance optimization is presented by EnergyConstrained Performance Optimal Static Scheduling (ECPOSS) algorithm which canreduce the execution time by loop rescheduling within a given energy constraint. Theoptimalities of EOSS and ECPOSS have been proved. The experiment results validatethe effectiveness of the above algorithms.The energy optimization of interconnection network has an important meaning forenergy optimization of the whole system. Static energy consumption occupies the mainpart of interconnection network energy consumption. The important technique to reducethe static energy consumption is shutting down network components. This thesis proposes energy optimization of interconnection network based on network topologypartition. Firstly, the thesis analyzes the occupancy characteristics of interconnectionnetwork in space and time dimension followed by the concept of network topologypartition based on routing rule. Then the thesis proposes network topology partitionmethods for Nd-mesh, Nd-torus and fat-tree network with three kinds of routing rule:determinate routing, oblivious adaptive routing and full adaptive routing. Finaly, thethesis describes the key techniques of static energy management for interconnectionnetwork based on network topology partition which shut down routers in space and timedimension. Within the software framwork of TH-1A, the scheme of static energymanagement of interconection network has been proposed with which the virtual-actualcombined experimental environment is constructed. A large amount of experiment hasproven the effectiveness of it.The main contributions of this thesis are as follows.1. Propose the energy optimization guided parallel loop scheduling methods. Fromthe viewpoint of performance-constrained energy optimization and energy-constrainedperformance optimization, the thesis represents two kinds of OpenMP loop schedulingenergy optimization algorithms, among which the representative two algorithms areEnergy Saving Optimal Static Scheduling (EOSS) and Energy ConstrainedPerformance Optimal Static Scheduling (ECPOSS). The optimalities of these twoalgorithms are proved. The experiment results validate the effectiveness of these twokinds of algorithms.2. Propose the ideology of router shutting down based on interconnection networktopology partition. The thesis analyzes the direct and indirect occupancy of parallel jobson routers in space dimension, and the continual occupancy on routers in timedimension. The independent occupancy of multip-jobs on routers is also analysed whichis followed by the concept of network topology partition--it can instruct the shuttingdown of routers.3. Propose the network topology partion methods for typical network with typicalrouting rules. The network topology partition methods for Nd-mesh, Nd-torus andfat-tree network with three kinds of routing rule: determinate routing, oblivious adaptiverouting and full adaptive routing are presented.4. The key techniques for static energy management based on interconnectionnetwork topology partition are proposed including the setting of regions in which therouters cannot be powered off, topology-awared resource allocation policy and spacialfragments management. Under the software framework of TH-1A, the thesis proposeand implements scheme of the network topology partition based interconnectionnetwork static energy management with which the virtual-actual combined experimental environment is constructed. The experimental results validate the effectiveness ofenergy optimization of interconnection network.