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A Utility Based Power-Aware Autonomic Approach for Running Scientific Applications

A Utility Based Power-Aware Autonomic Approach for Running S...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Mehrotra, Rajat Banicescu, Ioana Srivastava, Srishti Mississippi State Univ NSF Ctr Auton Comp Dept Elect & Comp Engn Mississippi State MS 39762 USA Mississippi State Univ NSF Ctr Auton Comp Dept Comp Sci & Engn Starkville MS USA

ISBN: (纸本)9780769546766

Traditionally, computational power and performance of the high performance computing (HPC) systems are assumed to depend upon the number of processors and speed of supercomputers. Supercomputers run at their peak performance to efficiently execute scientific applications. Therefore, these supercomputers consume enormous amount of power that results in increased operational cost. The high power consumption translates into high temperature of the physical HPC systems, which in turn results in high failure rate and decreased reliability. Employing an aggressive cooling system does not improve the situation, because it involves an additional operational and infrastructure cost. Slowing down these HPC systems results in loss of performance that is also not recommended. Moreover, the execution of scientific applications is affected adversely through the variation in available computational resources. This variation is due to the computational resource utilization by other applications running at the computing nodes. Therefore, the execution of a scientific application should be monitored with respect to its performance objectives (deadline etc.). Failure in meeting the deadlines may result in high cost in terms of revenue loss to the service providers. These issues raise the motivation towards the designing of an autonomic approach for managing power consumption in HPC systems without adversely affecting to the performance of the system. In this paper, we present a utility based power-aware approach that uses a model-based control theoretic framework for executing scientific applications. The approach and related simulations indicate that the performance and the power requirements of the system can dynamically be adjusted, while maintaining the predefined quality of service (QoS) goals in terms of deadline of execution and power consumption of the HPC system, even in the presence of computational resource related perturbations. This approach is autonomic, performance dire

关键词： High Performance computing Legal Executions Power consumption supercomputer power requirement failure rates peak performance

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A Fast parallel Implementation of Molecular Dynamics with the Morse Potential on a Heterogeneous Petascale Supercomputer

A Fast Parallel Implementation of Molecular Dynamics with th...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Wu, Qiang Yang, Canqun Wang, Feng Xue, Jingling Natl Univ Def Technol Sch Comp Sci Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9780769546766

Molecular Dynamics (MD) simulations have been widely used in the study of macromolecules. To ensure an acceptable level of statistical accuracy relatively large number of particles are needed, which calls for high performance implementations of MD. These days heterogeneous systems, with their high performance potential, low power consumption, and high price-performance ratio, offer a viable alternative for running MD simulations. In this paper we introduce a fast parallel implementation of MD simulation with the Morse potential on Tianhe-1A, a petascale heterogeneous supercomputer. Our code achieves a speedup of 3.6x on one NVIDIA Tesla M2050 GPU (containing 14 Streaming Multiprocessors) compared to a 2.93GHz six-core Intel Xeon X5670 CPU. In addition, our code runs faster on 1024 compute nodes (with two CPUs and one GPU inside a node) than on 4096 GPU-excluded nodes, effectively rendering one GPU more efficient than six six-core CPUs. Our work shows that large-scale MD simulations can benefit enormously from GPU acceleration in petascale supercomputing platforms. Our performance results are achieved by using (1) a patch-cell design to exploit parallelism across the simulation domain, (2) a new GPU kernel developed by taking advantage of Newton's Third Law to reduce redundant force computation on GPUs, (3) two optimization methods including a dynamic load balancing strategy that adjusts the workload, and a communication overlapping method to overlap the communications between CPUs and GPUs.

关键词： Molecular Dynamics heterogeneous computing petascale supercomputer GPU computing

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parallel Pair-HMM SNP Detection

Parallel Pair-HMM SNP Detection

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Clement, Nathan L. Shepherd, Brent A. Bodily, Paul Tumur-Ochir, Sukhbat Gim, Younghoon Snell, Quinn Clement, Mark J. Johnson, W. Evan Univ Texas Austin Dept Comp Sci Austin TX 78701 USA Brigham Young Univ Dept Comp Sci Provo UT 84602 USA Brigham Young Univ Dept Stat Provo UT 84602 USA Brigham Young Univ Dept Med Provo UT 84602 USA

ISBN: (纸本)9780769546766

I. MOTIVATION: Due to the massive amounts of data generated from each instrument run, next generation sequencing technologies have presented researchers with unique analytical challenges which require innovative, computationally efficient statistical solutions. Here we present a parallel implementation of a probabilistic Pair-Hidden Markov Model for base calling and SNP detection in next generation sequencing data. Our approach incorporates multiple sources of error into the base calling procedure which leads to more accurate results. In addition, our approach applies a likelihood ratio test that provides researchers with straightforward SNP calling cutoffs based on a p-value cutoff or a false discovery control. II. RESULTS: We have developed GNUMAP-SNP, which is a highly accurate approach for the identification of SNPs in next generation sequencing data. By utilizing a novel probabilistic Pair-Hidden Markov Model, GNUMAP-SNP effectively accounts for uncertainty in the read calls as well as read mapping in an unbiased fashion. Our results show that GNUMAP-SNP has both high sensitivity and high specificity throughout the genome, which is especially true in repeat regions or in areas with low read coverage. In addition, we propose a statistical framework that accounts for the background noise using straightforward statistical cutoffs which filters out false-positive results. The parallel implementation of SNP calling achieves near linear speedup on distributed memory or shared memory platforms. III. AVAILABILITY: GNUMAP-SNP is available as a module in the GNUMAP probabilistic read mapping software. GNUMAP is freely available for download at: http://***/gnumap/

关键词： next-generation sequencing short-read mapping sequence mappers parallel computing biology computing

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Thermal-Aware Performance Optimization in Power Constrained Heterogeneous Data Centers

Thermal-Aware Performance Optimization in Power Constrained ...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Al-Qawasmeh, Abdulla M. Pasricha, Sudeep Maciejewski, Anthony A. Siegel, Howard Jay Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA

ISBN: (纸本)9780769546766

The power consumption of data centers has been increasing at a rapid rate over the past few years. Many of these data centers experience physical limitations on the power needed to run the data center. This paper attempts to maximize the performance of a data center that is subject to total power consumption and thermal constraints. We consider a power model for a data center that includes power consumed in both Computer Room Air Conditioning (CRAC) units and compute nodes. Our approach quantifies the performance of the data center as the total reward collected from completing tasks in a workload by their individual deadlines. We develop novel optimization techniques for assigning the performance states of compute cores at the data center level to increase the performance of the data center. The assignment problem in this paper is thermal aware as it considers the temperature evolution effects of performance state assignments, which in turn affects the power consumed by the CRAC units. Our simulation studies show that in some cases the assignment technique used in this paper achieves about 10% average improvement in the performance of a data center over an assignment problem that only considers putting a compute core in the performance state with the highest performance or turning the core off.

关键词： Thermal-Aware Performance States Data Center CRAC heterogeneous computing

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Reliable Migration Module in Trusted Cloud based on Security Level - Design and Implementation

Reliable Migration Module in Trusted Cloud based on Security...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Chen, Ying Shen, Qingni Sun, Pengfei Li, Yangwei Chen, Zhong Qing, Sihan Peking Univ Sch Software & Microelect Beijing 100871 Peoples R China

ISBN: (纸本)9780769546766

Infrastructure as a Service (IaaS), basically consists on the deliverance of virtual machines (VMs) to an IaaS provider, who can rise or shrink the number of VMs so as to offer fast and easy scalability according to variable workloads. However, according to the principle of Buckets Effect, the safety of the entire system relies on its most fragile component. This problem also exists in IaaS cloud. There are many VMs which co-exist in the same physical machine, but they may adopt different security protection. So this could lead VMs with the higher security requirement degrade to the lowest security level. In order to address these issues, we propose Trusted Cloud based on Security Level (TCSL), which is an integrated, secured and trusted architecture based on logical VMs' union, to separate the VMs with different sensitive and security needs from the whole cloud environment, and to meet different customer's security requirements. Experimental results demonstrate that these approaches are effective in isolating the resources with the same security requirements in a shared trusted zone which is built based on different security level. When resources need to migrate to the trusted zone, the Reliable Migration Policies will be automatically enforced and match the migrating resource to an applicable trusted zone in cloud or return a feedback concerning a suggestion. With Reliable Migration Protocol, the secure process of the migrating transaction can be guaranteed in IaaS cloud.

关键词： Cloud computing IaaS Trusted Cloud Migration Security

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distributed Transactional Memory for General Networks

Distributed Transactional Memory for General Networks

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Sharma, Gokarna Busch, Costas Srinivasagopalan, Srivathsan Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA

ISBN: (纸本)9780769546759

We consider the problem of implementing transactional memory in large-scale distributed networked systems. We present and analyze Spiral, a novel distributed directory-based protocol for transactional memory. Spiral is designed for the data-flow distributed implementation of software transactional memory which supports three basic operations: publish, allowing a shared object to be inserted in the directory so that other nodes can find it;lookup, providing a read-only copy of the object to the requesting node;move, allowing the requesting node to write the object locally after the node gets it. The protocol runs on a hierarchical directory construction based on sparse covers, where clusters at each level are ordered to avoid race conditions while serving concurrent requests. Given a shared object the protocol maintains a directory path pointing to the object. The basic idea is to use "spiral" paths that grow outward to search for the directory path of the object in a bottom-up fashion. For general networks, this protocol guarantees an O(log(2) n . log D) approximation for move requests, where n is the number of nodes and D is the diameter of the network. It also guarantees poly-log approximation for lookup requests. To the best of our knowledge, this is the first consistency protocol for distributed transactional memory that achieves poly-log approximation in general networks.

关键词： distributed transactional memory Cache-coherence Hierarchical clustering Stretch General network

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distributed Demand and Response Algorithm for Optimizing Social-Welfare in Smart Grid

Distributed Demand and Response Algorithm for Optimizing Soc...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Dong, Qifen Yu, Li Song, Wen-Zhan Tong, Lang Tang, Shaojie Zhejiang Univ Technol Coll Informat Engn Hangzhou Zhejiang Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA IIT Dept Comp Sci Chicago IL 60616 USA

ISBN: (纸本)9780769546759

This paper presents a distributed Demand and Response algorithm for smart grid with the objective of optimizing social-welfare. Assuming the power demand range is known or predictable ahead of time, our proposed distributed algorithm will calculate demand and response of all participating energy demanders and suppliers, as well as energy flow routes, in a fully distributed fashion, such that the social-welfare is optimized. During the computation, each node (e. g., demander or supplier) only needs to exchange limited rounds of messages with its neighboring nodes. It provides a potential scheme for energy trade among participants in the smart girds. Our theoretical analysis proves that the algorithm converges even if there is some random noise induced in the process of our distributed Lagrange-Newton based solution. The simulation also shows that the result is close to that of centralized solution.

关键词： Demand Response Lagrange-Newton method distributed Social-Welfare

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Predicting Potential Speedup of Serial Code via Lightweight Profiling and Emulations with Memory Performance Model

Predicting Potential Speedup of Serial Code via Lightweight ...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Kim, Minjang Kumar, Pranith Kim, Hyesoon Brett, Bevin Georgia Inst Technol Coll Comp Sch Comp Sci Atlanta GA 30332 USA Intel Corp Software & Serv Grp Santa Clara CA 95051 USA

ISBN: (纸本)9780769546759

We present parallel Prophet, which projects potential parallel speedup from an annotated serial program before actual parallelization. Programmers want to see how much speedup could be obtained prior to investing time and effort to write parallel code. With parallel Prophet, programmers simply insert annotations that describe the parallel behavior of the serial program. parallel Prophet then uses lightweight interval profiling and dynamic emulations to predict potential performance benefit. parallel Prophet models many realistic features of parallel programs: unbalanced workload, multiple critical sections, nested and recursive parallelism, and specific thread schedulings and paradigms, which are hard to model in previous approaches. Furthermore, parallel Prophet predicts speedup saturation resulting from memory and caches by monitoring cache hit ratio and bandwidth consumption in a serial program. We achieve very small runtime overhead: approximately a 1.2-10 times slowdown and moderate memory consumption. We demonstrate the effectiveness of parallel Prophet in eight benchmarks in the OmpSCR and NAS parallel benchmarks by comparing our predictions with actual parallelized code. Our simple memory model also identifies performance limitations resulting from memory system contention.

关键词： parallel Lines Speeding simulating Memory Memory BENCHMARKS Serial Publications Codes ANNOTATIONS Cache memory Compare Cache Memory System

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A Self-tuning Failure Detection Scheme for Cloud computing Service

A Self-tuning Failure Detection Scheme for Cloud Computing S...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Xiong, Naixue Vasilakos, Athanasios V. Wu, Jie Yang, Y. Richard Rindos, Andy Zhou, Yuezhi Song, Wen-Zhan Pan, Yi Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA Univ Western Macedonia Dept Comp & Tele Engn kozanki Greece Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Yale Univ Dept Comp Sci New Haven CT 06520 USA IBM Corp Dept Bldg 503 Durham NC USA Tsinghua Univ Dept Comp Sci & Tech Beijing Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

ISBN: (纸本)9780769546759

Cloud computing is an increasingly important solution for providing services deployed in dynamically scalable cloud networks. Services in the cloud computing networks may be virtualized with specific servers which host abstracted details. Some of the servers are active and available, while others are busy or heavy loaded, and the remaining are offline for various reasons. Users would expect the right and available servers to complete their application requirements. Therefore, in order to provide an effective control scheme with parameter guidance for cloud resource services, failure detection is essential to meet users' service expectations. It can resolve possible performance bottlenecks in providing the virtual service for the cloud computing networks. Most existing Failure Detector (FD) schemes do not automatically adjust their detection service parameters for the dynamic network conditions, thus they couldn't be used for actual application. This paper explores FD properties with relation to the actual and automatic fault-tolerant cloud computing networks, and find a general non-manual analysis method to self-tune the corresponding parameters to satisfy user requirements. Based on this general automatic method, we propose a specific and dynamic Self-tuning Failure Detector, called SFD, as a major breakthrough in the existing schemes. We carry out actual and extensive experiments to compare the quality of service performance between the SFD and several other existing FDs. Our experimental results demonstrate that our scheme can automatically adjust SFD control parameters to obtain corresponding services and satisfy user requirements, while maintaining good performance. Such an SFD can be extensively applied to industrial and commercial usage, and it can also significantly benefit the cloud computing networks.

关键词： Application requirements Cloud computing service Fault tolerance Quality of service Self-tuning failure detection

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A parallel Packet Processing Runtime System On Multi-Core Network Processors

A Parallel Packet Processing Runtime System On Multi-Core Ne...

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11th international symposium on distributed computing and Applications to Business, Engineering and Science (DCABES)

作者： Li, Yunchun Shan, Lianqiang Qiao, Xinxin BeiHang Univ Beijing Beijing Key Lab Network Technol Dept Comp Sci Beijing Peoples R China

ISBN: (纸本)9780769548180

More and more network devices and chips commonly apply multi-core architectures to meet increasingly performance demands. But the lack of efficient program level parallelism and workload allocation in the packet processing system greatly limits the utilization of multi-core architectures. In this paper, we propose a parallel packet processing runtime system and explore an affinity-based packet scheduler with the goal of raising load balancing and decreasing cache miss. We can use the system that handles the allocation of processing tasks to simplify the implementation of new applications. The experiment results show task distributor and scheduler can achieve a better compromise between load balancing and cache affinity in the parallel packet processing system.

关键词： multi-core load banlance parallel packet process

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