2014 IEEE 28th International Parallel and Distributed Processing Symposium最新文献_第5页

A Framework for Lattice QCD Calculations on GPUs 基于gpu的点阵QCD计算框架

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.112

F. Winter, M. Clark, R. Edwards, B. Joó

{"title":"A Framework for Lattice QCD Calculations on GPUs","authors":"F. Winter, M. Clark, R. Edwards, B. Joó","doi":"10.1109/IPDPS.2014.112","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.112","url":null,"abstract":"Computing platforms equipped with accelerators like GPUs have proven to provide great computational power. However, exploiting such platforms for existing scientific applications is not a trivial task. Current GPU programming frameworks such as CUDA C/C++ require low-level programming from the developer in order to achieve high performance code. As a result porting of applications to GPUs is typically limited to time-dominant algorithms and routines, leaving the remainder not accelerated which can open a serious Amdahl's law issue. The Lattice QCD application Chroma allows us to explore a different porting strategy. The layered structure of the software architecture logically separates the data-parallel from the application layer. The QCD Data-Parallel software layer provides data types and expressions with stencil-like operations suitable for lattice field theory. Chroma implements algorithms in terms of this high-level interface. Thus by porting the low-level layer one effectively ports the whole application layer in one swing. The QDP-JIT/PTX library, our reimplementation of the low-level layer, provides a framework for Lattice QCD calculations for the CUDA architecture. The complete software interface is supported and thus applications can be run unaltered on GPU-based parallel computers. This reimplementation was possible due to the availability of a JIT compiler which translates an assembly language (PTX) to GPU code. The existing expression templates enabled us to employ compile-time computations in order to build code generators and to automate the memory management for CUDA. Our implementation has allowed us to deploy the full Chroma gauge-generation program on large scale GPU-based machines such as Titan and Blue Waters and accelerate the calculation by more than an order of magnitude.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125851930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 34

High Performance Alltoall and Allgather Designs for InfiniBand MIC Clusters InfiniBand MIC集群的高性能Alltoall和Allgather设计

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.72

Akshay Venkatesh, S. Potluri, R. Rajachandrasekar, Miao Luo, Khaled Hamidouche, D. Panda

{"title":"High Performance Alltoall and Allgather Designs for InfiniBand MIC Clusters","authors":"Akshay Venkatesh, S. Potluri, R. Rajachandrasekar, Miao Luo, Khaled Hamidouche, D. Panda","doi":"10.1109/IPDPS.2014.72","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.72","url":null,"abstract":"Intel's Many-Integrated-Core (MIC) architecture aims to provide Teraflop throughput (through high degrees of parallelism) with a high FLOP/Watt ratio and x86 compatibility. However, this two-fold approach to solving power and programmability challenges for Exascale computing is constrained by certain architectural idiosyncrasies. MIC coprocessors have a memory constrained environment and its processors operate at slower clock rates. Also, being PCI devices, the communication characteristics of MIC co-processors are different compared to communication behavior seen in homogeneous environments. For instance, the performance of sending data from the MIC memory to a remote node's memory through message passing routines has 3x-6x higher latency than sending from the host processor memory. Hence communication libraries that do not consider these architectural subtleties are likely to nullify performance benefits or even cause degradation in applications that intend to use MICs and rely heavily on communication routines. The performance of Message Passing Interface (MPI) operations, especially dense collective operations like All-to-all and All gather, strongly affect the performance of many distributed parallel applications. In this paper, we revisit state-of-the-art algorithms commonly used to implement All-to-all collectives and propose adaptations and optimizations to alleviate architectural bottlenecks on MIC clusters. We also propose a few novel designs to improve the communication latency of these operations. Through micro-benchmarks and applications, we substantiate the benefits of incorporating the proposed adaptations to the All-to-All collective operations. At the micro-benchmark level, the proposed designs show as much as 79% improvement for All gather operation and up to 70% improvement for All-to-all and with the P3DFFT application, an improvement of 38% is seen in overall execution time.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129961830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Balancing On-Chip Network Latency in Multi-application Mapping for Chip-Multiprocessors 在芯片多处理器多应用映射中平衡片上网络延迟

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.94

Di Zhu, Lizhong Chen, Siyu Yue, T. Pinkston, Massoud Pedram

引用次数: 11

Complex Network Analysis Using Parallel Approximate Motif Counting 基于并行近似基序计数的复杂网络分析

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.50

George M. Slota, Kamesh Madduri

{"title":"Complex Network Analysis Using Parallel Approximate Motif Counting","authors":"George M. Slota, Kamesh Madduri","doi":"10.1109/IPDPS.2014.50","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.50","url":null,"abstract":"Subgraph counting forms the basis of many complex network analysis metrics, including motif and anti-motif finding, relative graph let frequency distance, and graph let degree distribution agreements. Determining exact subgraph counts is computationally very expensive. In recent work, we present FASCIA, a shared-memory parallel algorithm and implementation for approximate subgraph counting. FASCIA uses a dynamic programming-based approach and is significantly faster than exhaustive enumeration, while generating high-quality approximations of subgraph counts. However, the memory usage of the dynamic programming step prohibits us from applying FASCIA to very large graphs. In this paper, we introduce a distributed-memory parallelization of FASCIA by partitioning the graph and the dynamic programming table. We discuss a new collective communication scheme to make the dynamic programming step memory-efficient. These optimizations enable scaling to much larger networks than before. We also present a simple parallelization strategy for distributed subgraph counting on smaller networks. The new additions let us use subgraph counts as graph signatures for a large network collection, and we analyze this collection using various subgraph count-based graph analytics.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115260078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

Cost-Optimal Execution of Boolean Query Trees with Shared Streams 具有共享流的布尔查询树的成本最优执行

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.13

H. Casanova, Lipyeow Lim, Y. Robert, F. Vivien, Dounia Zaidouni

引用次数: 6

Collaborative Network Configuration in Hybrid Electrical/Optical Data Center Networks 混合电/光数据中心网络中的协同网络配置

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.92

Zhiyang Guo, Yuanyuan Yang

{"title":"Collaborative Network Configuration in Hybrid Electrical/Optical Data Center Networks","authors":"Zhiyang Guo, Yuanyuan Yang","doi":"10.1109/IPDPS.2014.92","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.92","url":null,"abstract":"Recently, there has been much effort on introducing optical fiber communication to data center networks (DCNs) because of its significant advantage in bandwidth capacity and power efficiency. However, due to limitations of optical switching technologies, optical networking alone has not yet been able to accommodate the volatile data center traffic. As a result, hybrid packet/circuit (Hypac) switched DCNs, which argument the electrical packet switched (EPS) network with an optical circuit switched (OCS) network, have been proposed to combine the strengths of both types of networks. However, one problem with current Hypac DCNs is that the EPS network is shared in a best effort fashion and is largely oblivious to the accompanying OCS network, which results in severe drawbacks, such as degraded network predictability and deficiency in handling correlated traffic. Since the OCS/EPS networks have unique strengths and weaknesses, and are best suited for different traffic patterns, coordinating and collaborating the configuration of both networks is critical to reach the full potential of Hypac DCNs, which motivates the study in this paper. First, we present a network model that accurately abstracts the essential characteristics of the EPS/OCS networks. Second, considering the recent advances in network control technology, we propose a time-efficient algorithm called Collaborative Bandwidth Allocation (CBA) that configures both networks in a complementary manner. Finally, we conduct comprehensive simulations, which demonstrate that CBA significantly improves the performance of Hypac DCNs in many aspects.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126734586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Finding Motifs in Biological Sequences Using the Micron Automata Processor 利用微米自动机处理器寻找生物序列中的基序

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.51

Indranil Roy, S. Aluru

引用次数: 72

Heterogeneity-Aware Workload Placement and Migration in Distributed Sustainable Datacenters 分布式可持续数据中心中异构感知的工作负载放置和迁移

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.41

Dazhao Cheng, Changjun Jiang, Xiaobo Zhou

{"title":"Heterogeneity-Aware Workload Placement and Migration in Distributed Sustainable Datacenters","authors":"Dazhao Cheng, Changjun Jiang, Xiaobo Zhou","doi":"10.1109/IPDPS.2014.41","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.41","url":null,"abstract":"While major cloud service operators have taken various initiatives to operate their sustainable data enters with green energy, it is challenging to effectively utilize the green energy since its generation depends on dynamic natural conditions. Fortunately, the geographical distribution of data enters provides an opportunity for optimizing the system performance by distributing cloud workloads. In this paper, we propose a holistic heterogeneity-aware cloud workload placement and migration approach, sCloud, that aims to maximize the system good put in distributed self-sustainable data enters. sCloud adaptively places the transactional workload to distributed data enters, allocates the available resource to heterogeneous workloads in each data enter, and migrates batch jobs across data enters, while taking into account the green power availability and QoS requirements. We formulate the transactional workload placement as a constrained optimization problem that can be solved by nonlinear programming. Then, we propose a batch job migration algorithm to further improve the system good put when the green power supply varies widely at different locations. We have implemented sCloud in a university cloud test bed with real-world weather conditions and workload traces. Experimental results demonstrate sCloud can achieve near-to-optimal system performance while being resilient to dynamic power availability. It outperforms a heterogeneity-oblivious approach by 26% in improving system good put and 29% in reducing QoS violations.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114785220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 42

Communication-Efficient Distributed Variance Monitoring and Outlier Detection for Multivariate Time Series 多变量时间序列的高效通信分布式方差监测与离群点检测

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.16

Moshe Gabel, A. Schuster, D. Keren

{"title":"Communication-Efficient Distributed Variance Monitoring and Outlier Detection for Multivariate Time Series","authors":"Moshe Gabel, A. Schuster, D. Keren","doi":"10.1109/IPDPS.2014.16","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.16","url":null,"abstract":"Modern scale-out services are comprised of thousands of individual machines, which must be continuously monitored for unexpected failures. One recent approach to monitoring is latent fault detection, an adaptive statistical framework for scale-out, load-balanced systems. By periodically measuring hundreds of performance metrics and looking for outlier machines, it attempts to detect subtle problems such as misconfigurations, bugs, and malfunctioning hardware, before they manifest as machine failures. Previous work on a large, real-world Web service has shown that many failures are indeed preceded by such latent faults. Latent fault detection is an offline framework with large bandwidth and processing requirements. Each machine must send all its measurements to a centralized location, which is prohibitive in some settings and requires data-parallel processing infrastructure. In this work we adapt the latent fault detector to provide an online, communication- and computation-reduced version. We utilize stream processing techniques to trade accuracy for communication and computation. We first describe a novel communication-efficient online distributed variance monitoring algorithm that provides a continuous estimate of the global variance within guaranteed approximation bounds. Using the variance monitor, we provide an online distributed outlier detection framework for non-stationary multivariate time series common in scale-out systems. The adapted framework reduces data size and central processing cost by processing the data in situ, making it usable in wider settings. Like the original framework, our adaptation admits different comparison functions, supports non-stationary data, and provides statistical guarantees on the rate of false positives. Simulations on logs from a production system show that we are able to reduce bandwidth by an order of magnitude, with below 1% error compared to the original algorithm.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117180604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 31

Exploiting Geometric Partitioning in Task Mapping for Parallel Computers 并行计算机任务映射中的几何划分

2014 IEEE 28th International Parallel and Distributed Processing Symposium Pub Date : 2014-05-19 DOI: 10.1109/IPDPS.2014.15

Mehmet Deveci, S. Rajamanickam, V. Leung, K. Pedretti, Stephen L. Olivier, David P. Bunde, Ümit V. Çatalyürek, K. Devine

{"title":"Exploiting Geometric Partitioning in Task Mapping for Parallel Computers","authors":"Mehmet Deveci, S. Rajamanickam, V. Leung, K. Pedretti, Stephen L. Olivier, David P. Bunde, Ümit V. Çatalyürek, K. Devine","doi":"10.1109/IPDPS.2014.15","DOIUrl":"https://doi.org/10.1109/IPDPS.2014.15","url":null,"abstract":"We present a new method for mapping applications' MPI tasks to cores of a parallel computer such that communication and execution time are reduced. We consider the case of sparse node allocation within a parallel machine, where the nodes assigned to a job are not necessarily located within a contiguous block nor within close proximity to each other in the network. The goal is to assign tasks to cores so that interdependent tasks are performed by \"nearby\" cores, thus lowering the distance messages must travel, the amount of congestion in the network, and the overall cost of communication. Our new method applies a geometric partitioning algorithm to both the tasks and the processors, and assigns task parts to the corresponding processor parts. We show that, for the structured finite difference mini-app Mini Ghost, our mapping method reduced execution time 34% on average on 65,536 cores of a Cray XE6. In a molecular dynamics mini-app, Mini MD, our mapping method reduced communication time by 26% on average on 6144 cores. We also compare our mapping with graph-based mappings from the LibTopoMap library and show that our mappings reduced the communication time on average by 15% in MiniGhost and 10% in MiniMD.","PeriodicalId":309291,"journal":{"name":"2014 IEEE 28th International Parallel and Distributed Processing Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115076130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 69