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Battery-efficient task execution on reconfigurable computing platforms with multiple processing units

Battery-efficient task execution on reconfigurable computing...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Khan, Jawad Vemuri, Ranga University of Cincinnati ECECS Department ML30 Cincinnati OH 45221-0030 United States

ISBN: (纸本)0769523129

This paper presents a battery-efficient task execution methodology on Reconfigurable Computing (RC) Platforms which have multiple processing units. These processing units can be on-chip in the form of soft-processors, embedded processors or "Reconfigurable Tiles" where the reconfigurable area of an Field Programmable Gate Array (FPGA) is divided into fixed re configurable slots. processing units can also be off-chip in the form of individual FPGAs and voltage-scalable processors. An application is modeled in the form of a precedence task graph. We assume that for each task in the task graph several different design-points are available which correspond to different voltage-frequency combinations for processors and different hardware implementations for FPGAs and "Reconfigurable Tiles". It is assumed that performance and total power consumption estimates for each design-point are available for any given implementation, including the peripheral components such as memory and display power usage. First we present an iterative heuristic algorithm for a single processing unit, which finds a sequence of tasks along with an appropriate design-point for each task, such that a deadline is met and the amount of battery energy used is as small as possible. Next, we extend this algorithm to multiple processing units in an RC platform. We used several real-world benchmarks to test the effectiveness of this methodology. Each benchmark was executed on one, two, three and four processing units and its power utilization was characterized by implementing it on a portable RC Platform called iPACE-Vl[4], We present the results which show that choosing an appropriate execution mode is crucial for battery-efficient execution. We also show that parallel execution on multiple-processing units can actually be more battery-efficient than sequential execution on a single processing unit under certain circumstances.

关键词： parallel processing systems

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Grid environment for computational astrophysics driven by GRAPE-6 with HMCS-G and OmniRPC

Grid environment for computational astrophysics driven by GR...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Boku, Taisuke Onuma, Kenji Sato, Mitsuhisa Nakajima, Yoshihiro Takahashi, Daisuke Graduate School of Systems and Information Engineering University of Tsukuba Center for Computational Sciences University of Tsukuba Doctoral Program of Systems and Information Engineering University of Tsukuba

ISBN: (纸本)0769523129

In computational astrophysics, the effect of gravity is essential even with very heavy computation of O(N2) for N particles. Several special purpose machines have been implemented as gravity engine to handle this problem extremely fast, however there are few sites in the world to operate such systems. We have developed a grid environment to access such a system based on grid-RFC, named HMCS-G. Using HMCS-G, a multi-physical computational astrophysics simulation can be performed with the combination of a PC-cluster and the gravity engine GRAPE-6. In typical size of problems for galaxy formation, however, the computation power of PC-cluster is much weaker than that of GRAPE-6, and we need multiple sets of PC-clusters to share the power of GRAPE-6 on grid environment. We have developed such a system using OmniRPC, a grid-enabled RPC system. In this system, OmniRPC are used both to distribute jobs for parameter search on multiple PC-clusters and to access GRAPE-6 server from these clusters. We performed an actual problem to search several formations of galaxy on this system, and confirmed such a solution is useful for wide variety of computational astrophysics research.

关键词： distributed computer systems

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proceedings WiO5pt third International symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks

Proceedings WiO5pt Third International Symposium on Modeling...

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3rd International symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks 2005, WiOpt 2005

ISBN: (纸本)076952267X

The proceedings contain 45 papers. The topics discussed include: closed and open looped optimal control of buffer and energy of wireless device;on the transport capacity of Gaussian multiple access and broadcast channels;secure comparison of encrypted data in wireless sensor networks;minimum energy transmission scheduling subject to deadline constraints;distributed power allocation and scheduling for parallel channel wireless networks;distributed fair resource allocation in cellular networks in the presence of heterogeneous delays;a simulated annealing algorithms for energy-efficient sensor network design;and a new hybrid scheduling framework for asymmetric wireless environments with request repetition.

关键词： Mobile telecommunication systems

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Dynamic mapping in energy constrained heterogeneous computing systems

Dynamic mapping in energy constrained heterogeneous computin...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Kim, Jong-Kook Siegel, H.J. Maciejewski, Anthony A. Eigenmann, Rudolf Purdue University Electrical and Computer Engineering School West Lafayette IN 47907-1285 United States Colorado State University Electrical and Computer Engineering Dept. Colorado State University Computer Science Dept. Fort Collins CO 80523-1373 United States

ISBN: (纸本)0769523129

An ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. The wireless devices have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks), and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.

关键词： distributed computer systems

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A realistic network/application model for scheduling divisible loads on large-scale platforms

A realistic network/application model for scheduling divisib...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Marchal, L. Yang, Y. Casanova, H. Robert, Y. Laboratoire LIP CNRS-INRIA École Normale Supérieure de Lyon France Dept. of Computer Science and Engineering University of California San Diego United States San Diego Supercomputer Center University of California San Diego United States

ISBN: (纸本)0769523129

Divisible load applications consist of an amount of data and associated computation that can be divided arbitrarily into any number of independent pieces. This model is a good approximation of many real-world scientific applications, lends itself to a natural master-worker implementation, and has thus received a lot of attention. The issue of divisible load scheduling has been studied extensively. However, only a few authors have explored the simultaneous scheduling of multiple such applications on a distributed computing platform. We focus on this increasingly relevant scenario and make the following contributions. We use a novel and more realistic platform model that captures some of the fundamental network properties of grid platforms. We formulate the steady-state multi-application scheduling problem as a linear program that expresses a notion of fairness between applications. This scheduling problem is NP-complete and we propose several heuristics that we evaluate and compare via extensive simulation experiments. Our main finding is that some of our heuristics can achieve performance close to optimal and we quantify the trade-offs between achieved performance and heuristic complexity.

关键词： distributed computer systems

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Provable algorithms for parallel sweep scheduling on unstructured meshes

Provable algorithms for parallel sweep scheduling on unstruc...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Kumar, V. S. Anil Parthasarathy, Srinivasan Marathe, Madhav V. Srinivasan, Aravind Zust, Sibylle Los Alamos National Laboratory MS M997 Los Alamos NM 87545 Department of Computer Science University of Maryland College Park MD 20742 Virgnia Bio-informatics Institute Dept. of Computer Science Virginia Tech. Blacksburg VA Department of Computer Science UMIACS University of Maryland College Park MD 20742

ISBN: (纸本)0769523129

We present provably efficient parallel algorithms for sweep scheduling on unstructured meshes. Sweep scheduling is a commonly used technique in Radiation Transport problems, and involves inverting an operator by iteratively sweeping across a mesh. Each sweep involves solving the operator locally at each cell. However, each direction induces a partial order in which this computation can proceed. On a distributed computing system, the goal is to schedule the computation, so that the length of the schedule is minimized. Several heuristics have been proposed for this problem;see [14, 15] and the references therein;but none of the heuristics have worst case performance guarantees. Here we present a simple, almost linear time randomized algorithm which (provably) gives a schedule of length at most O(log2 n) times the optimal schedule for instances with n cells, when the communication cost is not considered, and a slight variant, which coupled with a much more careful analysis, gives a schedule of (expected) length O(log m log log log m) times the optimal schedule for m processors. These are the first such provable guarantees for this problem. We also design a priority based list schedule using these ideas, with the same theoretical guarantee, but much better performance in practice. We complement our theoretical results with extensive empirical analysis. The results show that (i) our algorithm performs very well and has significantly better performance guarantee in practice and (ii) the algorithm compares favorably with other natural and efficient parallel algorithms proposed in the literature [14, 15].

关键词： parallel processing systems

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DGMonitor: A performance monitoring tool for sandbox-based desktop grid platforms

DGMonitor: A performance monitoring tool for sandbox-based d...

引用

3rd International Workshop on Performance Modelling, Evaluation, and Optimization of parallel and distributed Systems held in Conjunction with the 18th International parallel and distributed processing symposium

作者： Cicotti, P Taufer, M Chien, AA Univ Calif San Diego Dept Comp Sci & Engn La Jolla CA 92093 USA Scripps Res Inst Dept Mol Biol La Jolla CA 92037 USA Univ Texas Dept Comp Sci El Paso TX 79968 USA

ISBN: (纸本)0769521320

Accurate, continuous resource monitoring and profiling are critical for enabling performance tuning and scheduling optimization. In desktop grid systems that employ sandboxing, these issues are challenging because (1) subjobs inside sandboxes are executed in a virtual computing environment and (2) the state of this virtual environment within the sandboxes is reset to an initial empty state after a subjob completion. DGMonitor is a monitoring tool which builds a global, accurate, and continuous view of real resource utilization for desktop grids with sandboxing. Our monitoring tool measures performance unobtrusively and reliably, uses a simple performance data model, and is easy to use. Our measurements demonstrate that DGMonitor can scale to large desktop grids (up to 12000 PCs) with low monitoring overhead in terms of resource consumption (less than 0.1% per machine). Though we originally developed DGMonitor with the Entropia DCGrid platform, our tool is easily portable and integrated into other desktop grid systems. In all of these systems, DGMonitor data can support existing and novel information services, particularly for performance tuning and scheduling. In this paper, the high scalability and monitoring power of DGMonitor are demonstrated with the Entropia DCGrid platform and the BOINC platform respectively.

关键词： performance monitoring and profiling sandboxing techniques distributed computing

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Security-driven heuristics and a fast genetic algorithm for trusted grid job scheduling

Security-driven heuristics and a fast genetic algorithm for ...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Song, Shanshan Kwok, Yu-Kwong Hwang, Kai University of Southern California Los Angeles CA 90089 United States Department of Computer Science University of Southern California Department of Electrical and Electronic Engineering HKU HKU University of Southern California IEEE Computer Society IEEE Communications Society IEEE Internet and Grid Computing Laboratory University of Southern California ITR GridSec Project USC

ISBN: (纸本)0769523129

In this paper, our contributions are two-fold: First, we enhance the Min-Min and Sufferage heuristics under three risk modes driven by security concerns. Second, we propose a new Space-Time Genetic Algorithm (STGA) for trusted job scheduling, which is very fast and easy to implement. Under our new model, a job can possibly fail if the site security level is lower than the job security demand. We consider three security-driven heuristic modes: secure, risky, and f-risky. The secure mode always dispatches jobs to secure sites meeting the job security demands. The risky mode allocates jobs to any available resource site, taking whatever the risk it may face. The f-risky mode tries to limit the risk to be at most certain probability f. Our extensive simulation results indicated that the proposed STGA is highly effective in scheduling two types of practical workloads: NAS (Numerical Aerodynamic Simulation) and PSA (parameter-sweep application). The STGA outperforms the Min-Min and Sufferage heuristics under three risk modes, in terms of a wide range of performance metrics including makespan, average response time, site utilization, slowdown ratio, and job failure rate.

关键词： distributed computer systems

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Fault-tolerant parallel applications with dynamic parallel schedules

Fault-tolerant parallel applications with dynamic parallel s...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Gerlach, Sebastian Hersch, Roger D. School of Computer and Communication Sciences Switzerland

ISBN: (纸本)0769523129

Commodity computer clusters are often composed of hundreds of computing nodes. These generally off-the-shelf systems are not designed for high reliability. Node failures therefore drive the MTBF of such clusters to unacceptable levels. The software frameworks used for running parallel applications need to be fault-tolerant in order to ensure continued execution despite node failures. We propose an extension to the flow graph based Dynamic parallel Schedules (DPS) development framework that allows non-trivial parallel applications to pursue their execution despite node failures. The proposed fault-tolerance mechanism relies on a set of backup threads located in the volatile storage of alternate nodes. These backup threads are kept up to date by duplication of the transmitted data objects and periodical checkpointing of thread states. In case of a failure, the current state of the threads that were on the failed node is reconstructed on the backup threads by re-executing operations. The corresponding valid re-execution order is automatically deduced from the data flow graph of the DPS application. Multiple simultaneous failures can be tolerated, provided that for each thread either the active thread or its corresponding backup thread survives. For threads that do not store a local state, an optimized mechanism eliminates the need for duplicate data object transmissions. The overhead induced by the fault tolerance mechanism consists mainly of duplicate data object transmissions that can, for compute bound applications, be carried out in parallel with ongoing computations. The increase in execution time due to fault tolerance therefore remains relatively low. It depends on the communication to computation ratio and on the parallel program's efficiency.

关键词： Fault tolerant computer systems

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Flexible particle swarm optimization tasks for reconfigurable processor arrays

Flexible particle swarm optimization tasks for reconfigurabl...

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19th ieee International parallel and distributed processing symposium, IPDPS 2005

作者： Janson, Stefan Middendorf, Martin Parallel Computing and Complex Systems Group Department of Computer Science University of Leipzig Augustusplatz 10/11 D-04109 Leipzig Germany

ISBN: (纸本)0769523129

Multi task parallel processor arrays are a common machine architecture in which, typically, the tasks running in parallel occupy disjoint subarrays of the machine. On dynamically and partially reconfigurable processor arrays the tasks can be changed during run time. This is useful for online scenarios when the relative importance of tasks might change and therefore the assignment of computational resources to the tasks should be changed. Examples are optimization tasks in an online scenario in which the results of some tasks are needed earlier than expected at initialization. For such tasks the size of their subarrays must be increased because they need more computational resources to speed up. In this paper we design flexible Particle Swarm Optimization (PSO) algorithms for 2-dimensional reconfigurable processor arrays where the algorithms can change their size and have a good optimization behaviour. Since PSO is an iterative, individual-based optimization algorithm that relies upon interactions of neighbouring particles suitable for fine-grained parallel architectures. We propose a dynamic 2-dimensional hierarchical ordering of the particles within a tasks subarray so that the best particles are concentrated in the center. This gives the best particles the strongest influence on the swarm. A further advantage is that size reductions of the tasks can easily be done by cutting off the outer parts of the swarm which contain mainly the less good particles. It is experimentally shown that the proposed algorithms perform better than standard PSO algorithms under conditions with varying supply of computing resources that are available for the tasks. Moreover, also for conditions with constant supply of processing resources and no need for size changes the proposed algorithms perform well.

关键词： Arrays

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