2015 44th International Conference on Parallel Processing最新文献_第2页

Matchmaking Applications and Partitioning Strategies for Efficient Execution on Heterogeneous Platforms 异构平台上高效执行的配对应用和分区策略

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.65

Jie Shen, A. Varbanescu, X. Martorell, H. Sips

{"title":"Matchmaking Applications and Partitioning Strategies for Efficient Execution on Heterogeneous Platforms","authors":"Jie Shen, A. Varbanescu, X. Martorell, H. Sips","doi":"10.1109/ICPP.2015.65","DOIUrl":"https://doi.org/10.1109/ICPP.2015.65","url":null,"abstract":"Heterogeneous platforms are mixes of different processing units. The key factor to their efficient usage is workload partitioning. Both static and dynamic partitioning strategies have been defined in previous work, but their applicability and performance differ significantly depending on the application to execute. In this paper, we propose an application-driven method to select the best partitioning strategy for a given workload. To this end, we define an application classification based on the application kernel structure -- i.e., The number of kernels in the application and their execution flow. We also enable five different partitioning strategies, which mix the best features of both static and dynamic approaches. We further define the performance-driven ranking of all suitable strategies for each application class. Finally, we match the best partitioning to a given application by simply determining its class and selecting the best ranked strategy for that class. We test the matchmaking on six representative applications, and demonstrate that the defined performance ranking is correct. Moreover, by choosing the best performing partitioning strategy, we can significantly improve application performance, leading to average speedup of 3.0x/5.3x over the Only-GPU/Only-CPU execution, respectively.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127816564","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: 7

Resident Block-Structured Adaptive Mesh Refinement on Thousands of Graphics Processing Units 基于数千个图形处理单元的驻留块结构自适应网格细化

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.15

D. Beckingsale, W. Gaudin, Andy Herdman, S. Jarvis

{"title":"Resident Block-Structured Adaptive Mesh Refinement on Thousands of Graphics Processing Units","authors":"D. Beckingsale, W. Gaudin, Andy Herdman, S. Jarvis","doi":"10.1109/ICPP.2015.15","DOIUrl":"https://doi.org/10.1109/ICPP.2015.15","url":null,"abstract":"Block-structured adaptive mesh refinement (AMR) is a technique that can be used when solving partial differential equations to reduce the number of cells necessary to achieve the required accuracy in areas of interest. These areas (shock fronts, material interfaces, etc.) are recursively covered with finer mesh patches that are grouped into a hierarchy of refinement levels. Despite the potential for large savings in computational requirements and memory usage without a corresponding reduction in accuracy, AMR adds overhead in managing the mesh hierarchy, adding complex communication and data movement requirements to a simulation. In this paper, we describe the design and implementation of a resident GPU-based AMR library, including: the classes used to manage data on a mesh patch, the routines used for transferring data between GPUs on different nodes, and the data-parallel operators developed to coarsen and refine mesh data. We validate the performance and accuracy of our implementation using three test problems and two architectures: an 8 node cluster, and 4,196 nodes of Oak Ridge National Laboratory's Titan supercomputer. Our GPU-based AMR hydrodynamics code performs up to 4.87× faster than the CPU-based implementation, and is scalable on 4,196 K20x GPUs using a combination of MPI and CUDA.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121370993","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: 19

LBM-IB: A Parallel Library to Solve 3D Fluid-Structure Interaction Problems on Manycore Systems 求解多核系统三维流固耦合问题的并行库

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.14

Prateek Nagar, Fengguang Song, Luoding Zhu, Lan Lin

{"title":"LBM-IB: A Parallel Library to Solve 3D Fluid-Structure Interaction Problems on Manycore Systems","authors":"Prateek Nagar, Fengguang Song, Luoding Zhu, Lan Lin","doi":"10.1109/ICPP.2015.14","DOIUrl":"https://doi.org/10.1109/ICPP.2015.14","url":null,"abstract":"Deformable structures are abundant in various domains such as biology, medicine, life sciences, and ocean engineering. Our previous work created a numerical method, named LBM-IB method [1], to solve the fluid-structure interaction (FSI) problems. Our LBM-IB method is particularly suitable for simulating flexible (or elastic) structures immersed in a moving viscous fluid. Fluid-structure interaction problems are well known for their heavy demands on computing resources. Today, it is still challenging to resolve many real-world FSI problems. In order to solve large-scale fluid-structure interactions more efficiently, in this paper, we design a parallel LBM-IB library on shared memory many core architectures. We start from a sequential version, which is extended to two different parallel versions. The paper first introduces the mathematical background of the LBM-IB method, then uses the sequential version as a ground to present our implemented computational kernels and the algorithm. Next, it describes the two parallel programs: an Open MP implementation and a cube-based parallel implementation using Pthreads. The cube-based implementation builds upon our new cube-centric algorithm where all the data are stored in cubes and computations are performed on individual cubes in a data-centric manner. By exploiting better data locality and fine-grain block parallelism, the cube-based parallel implementation is able to outperform the Open MP implementation by up to 53% on 64-core computer systems.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125161027","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: 10

What Is Wrong with the Transmission? A Comprehensive Study on Message Passing Related Bugs 变速器出了什么问题?消息传递相关bug的综合研究

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.50

Mingxing Zhang, Yongwei Wu, Kang Chen, Weimin Zheng

{"title":"What Is Wrong with the Transmission? A Comprehensive Study on Message Passing Related Bugs","authors":"Mingxing Zhang, Yongwei Wu, Kang Chen, Weimin Zheng","doi":"10.1109/ICPP.2015.50","DOIUrl":"https://doi.org/10.1109/ICPP.2015.50","url":null,"abstract":"Along with the prevalence of distributed systems, more and more applications require the ability of reliably transferring messages across a network. However, passing messages in a convenient and dependable way is both difficult and error prone. Thus the existing messaging products usually suffer from numerous software bugs. And these bugs are particularly difficult to be diagnosed or avoided. Therefore, in order to improve the methods for handling them, we need a better understanding of their characteristics. This paper provides the first (to the best of our knowledge)comprehensive characteristic study on message passing related bugs (MP-bugs). We have carefully examined the pattern, manifestation, fixing and other characteristics of 349 randomly selected real world MP-bugs from 3 representative open-source applications (Open MPI, Zero MQ, and Active MQ). Surprisingly, we found that nearly 60% of the non-latent MP-bugs can be categorised into two simple patterns: the message level bugs and the connection level bugs, which implies a promising perspective of detecting/tolerating tools for MP-bugs. Apart from this finding, our study have also uncovered many new (and sometimes surprising)insights of the message passing systems' developing process. The results should be useful for the design of corresponding bug detecting, exposing and tolerating tools.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131287677","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: 2

Sheriff: A Regional Pre-alert Management Scheme in Data Center Networks 治安官:数据中心网络的区域预警管理方案

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.76

Xiaofeng Gao, Wen Xu, Fan Wu, Guihai Chen

{"title":"Sheriff: A Regional Pre-alert Management Scheme in Data Center Networks","authors":"Xiaofeng Gao, Wen Xu, Fan Wu, Guihai Chen","doi":"10.1109/ICPP.2015.76","DOIUrl":"https://doi.org/10.1109/ICPP.2015.76","url":null,"abstract":"As the base infrastructure to support various cloud services, data center draws more and more attractions from both academia and industry. A stable, effective, and robust data center network (DCN) management system is urgently required from institutions and corporations. However, existing management schemes have several problems, including the difficulty to manage the entire network with heterogeneous network components by a centralized controller, and the short-sighted mechanism to deal with resource allocation, congestion control, and VM migration. In this paper, we design Sheriff: a distributed pre-alert and management scheme for DCN management. Sheriff is a regional self-automatic control scheme at end host side to balance network traffic and workload. It includes two phases: prediction and management. Each end-host predicts possible overload and congestion by prediction strategy based on ARIMA and Neural Network methodology, and perform an Alert message. Delegated local controllers then monitor their dominating region and activate localized protocols VmMigration to manage the network. We illustrate the predication accuracy by network traces from a local data center service provider, examine the management efficiency by simulations on both Fat-Tree topology and Bcube topology, and prove that VmMigration is an approximation with ratio 3+2/p where p is a constant predefined in local search algorithm. Both numerical simulations and theoretical analysis validate the efficiency of our design. In all, Sheriff is a fast and effective scheme to better improve the performance of DCN.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132785275","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: 1

RepFD - Using Reputation Systems to Detect Failures in Large Dynamic Networks 使用信誉系统来检测大型动态网络中的故障

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.18

M. Veron, O. Marin, Sébastien Monnet, Pierre Sens

引用次数: 8

Designing a Hybrid Scale-Up/Out Hadoop Architecture Based on Performance Measurements for High Application Performance 设计一个基于高性能应用性能测量的混合Scale-Up/Out Hadoop架构

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.11

Zhuozhao Li, Haiying Shen

{"title":"Designing a Hybrid Scale-Up/Out Hadoop Architecture Based on Performance Measurements for High Application Performance","authors":"Zhuozhao Li, Haiying Shen","doi":"10.1109/ICPP.2015.11","DOIUrl":"https://doi.org/10.1109/ICPP.2015.11","url":null,"abstract":"Since scale-up machines perform better for jobs with small and median (KB, MB) data sizes while scale-out machines perform better for jobs with large (GB, TB) data size, and a workload usually consists of jobs with different data size levels, we propose building a hybrid Hadoop architecture that includes both scale-up and scale-out machines, which however is not trivial. The first challenge is workload data storage. Thousands of small data size jobs in a workload may overload the limited local disks of scale-up machines. Jobs from scale-up and scale-out machines may both request the same set of data, which leads to data transmission between the machines. The second challenge is to automatically schedule jobs to either scale-up or scale-out cluster to achieve the best performance. We conduct a thorough performance measurement of different applications on scale-up and scale-out clusters, configured with Hadoop Distributed File System (HDFS) and a remote file system (i.e., OFS), respectively. We find that using OFS rather than HDFS can solve the data storage challenge. Also, we identify the factors that determine the performance differences on the scale-up and scale-out clusters and their cross points to make the choice. Accordingly, we design and implement the hybrid scale-up/out Hadoop architecture. Our trace-driven experimental results show that our hybrid architecture outperforms both the traditional Hadoop architecture with HDFS and with OFS in terms of job completion time.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"330 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134071961","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: 23

PPM: A Partitioned and Parallel Matrix Algorithm to Accelerate Encoding/Decoding Process of Asymmetric Parity Erasure Codes PPM:一种加速非对称奇偶校验纠删码编解码过程的分割并行矩阵算法

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.55

Shiyi Li, Q. Cao, Shenggang Wan, Wenhui Zhang, C. Xie, Xubin He, P. Subedi

引用次数: 2

Cache Coherence Protocol and Memory Performance of the Intel Haswell-EP Architecture Intel Haswell-EP架构的缓存一致性协议和内存性能

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.83

Daniel Molka, D. Hackenberg, R. Schöne, W. Nagel

引用次数: 67

Executing Large Scale Scientific Workflow Ensembles in Public Clouds 在公共云中执行大规模科学工作流集成

2015 44th International Conference on Parallel Processing Pub Date : 2015-09-01 DOI: 10.1109/ICPP.2015.61

Qingye Jiang, Young Choon Lee, Albert Y. Zomaya

{"title":"Executing Large Scale Scientific Workflow Ensembles in Public Clouds","authors":"Qingye Jiang, Young Choon Lee, Albert Y. Zomaya","doi":"10.1109/ICPP.2015.61","DOIUrl":"https://doi.org/10.1109/ICPP.2015.61","url":null,"abstract":"Scientists in different fields, such as high energy physics, earth science, and astronomy are developing large-scale workflow applications. In many use cases, scientists need to run a set of interrelated but independent workflows (i.e., Workflow ensembles) for the entire scientific analysis. As a workflow ensemble usually contains many sub-workflows in each of which hundreds or thousands of jobs exist with precedence constraints, the execution of such a workflow ensemble makes a great concern with cost even using elastic and pay-as-you-go cloud resources. In this paper, we address two main challenges in executing large-scale workflow ensembles in public clouds with both cost and deadline constraints: (1) execution coordination, and (2) resource provisioning. To this end, we develop a new pulling based workflow execution system with a profiling-based resource provisioning strategy. The idea is homogeneity in both scientific workflows and cloud resources can be exploited to remove scheduling overhead (in execution coordination) and to minimize cost meeting deadline. Our results show that our solution system can achieve 80% speed-up, by removing scheduling overhead, compared to the well-known Pegasus workflow management system when running scientific workflow ensembles. Besides, our evaluation using Montage (an astronomical image mosaic engine) workflow ensembles on around 1000-core Amazon EC2 clusters has demonstrated the efficacy of our resource provisioning strategy in terms of cost effectiveness within deadline.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124427483","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: 25