2022 21st International Symposium on Parallel and Distributed Computing (ISPDC)最新文献

Cuckoo Node Hashing on GPUs gpu上的布谷鸟节点哈希

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00013

Muhammad Javed, Hao Zhou, David Troendle, Byunghyun Jang

引用次数: 0

Workload Deployment and Configuration Reconciliation at Scale in Kubernetes-Based Edge-Cloud Continuums 基于kubernetes的边缘云连续体中的大规模工作负载部署和配置协调

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00026

D. Hass, Josef Spillner

{"title":"Workload Deployment and Configuration Reconciliation at Scale in Kubernetes-Based Edge-Cloud Continuums","authors":"D. Hass, Josef Spillner","doi":"10.1109/ISPDC55340.2022.00026","DOIUrl":"https://doi.org/10.1109/ISPDC55340.2022.00026","url":null,"abstract":"Continuum computing promises the abstraction of physical node location and node platform stack in order to create a seamless application deployment and execution across edges and cloud data centres. For industrial IoT applications, the demand to generate data insights in conjunction with an installed base of increasingly capable edge devices is calling for appropriate continuum computing interfaces. Derived from a case study in industrial water flow monitoring and based on the industry’s de-facto standard Kubernetes to deploy complex containerised workloads, we present an appropriate continuum deployment mechanism based on custom Kubernetes controllers and CI/CD, called Kontinuum Controller. Through synthetic experiments and a holistic cross-provider deployment, we investigate its scalability with emphasis on reconciling adjusted configuration per application and per node, a critical requirement by industrial customers. Our findings convey that Kubernetes by default would enter undesirable oscillation already for modestly sized deployments. Thus, we also discuss possible solutions.","PeriodicalId":389334,"journal":{"name":"2022 21st International Symposium on Parallel and Distributed Computing (ISPDC)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122771608","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

A hybrid clustering algorithm for high-performance edge computing devices [Short] 一种高性能边缘计算设备的混合聚类算法

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00020

G. Laccetti, M. Lapegna, D. Romano

引用次数: 2

A scalable algorithm for homomorphic computing on multi-core clusters 多核集群上同态计算的可扩展算法

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00017

F. Gava, L. Bayati

引用次数: 1

Estimating the Impact of Communication Schemes for Distributed Graph Processing 估计通信方案对分布式图处理的影响

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00016

Tian Ye, S. Kuppannagari, C. Rose, Sasindu Wijeratne, R. Kannan, V. Prasanna

{"title":"Estimating the Impact of Communication Schemes for Distributed Graph Processing","authors":"Tian Ye, S. Kuppannagari, C. Rose, Sasindu Wijeratne, R. Kannan, V. Prasanna","doi":"10.1109/ISPDC55340.2022.00016","DOIUrl":"https://doi.org/10.1109/ISPDC55340.2022.00016","url":null,"abstract":"Extreme scale graph analytics is imperative for several real-world Big Data applications with the underlying graph structure containing millions or billions of vertices and edges. Since such huge graphs cannot fit into the memory of a single computer, distributed processing of the graph is required. Several frameworks have been developed for performing graph processing on distributed systems. The frameworks focus primarily on choosing the right computation model and the partitioning scheme under the assumption that such design choices will automatically reduce the communication overheads. For any computational model and partitioning scheme, communication schemes — the data to be communicated and the virtual interconnection network among the nodes — have significant impact on the performance. To analyze this impact, in this work, we identify widely used communication schemes and estimate their performance. Analyzing the trade-offs between the number of compute nodes and communication costs of various schemes on a distributed platform by brute force experimentation can be prohibitively expensive. Thus, our performance estimation models provide an economic way to perform the analyses given the partitions and the communication scheme as input. We validate our model on a local HPC cluster as well as the cloud hosted NSF Chameleon cluster. Using our estimates as well as the actual measurements, we compare the communication schemes and provide conditions under which one scheme should be preferred over the others.","PeriodicalId":389334,"journal":{"name":"2022 21st International Symposium on Parallel and Distributed Computing (ISPDC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114227248","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: 0

Sponsors and Conference Support 赞助商和会议支持

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/icbake.2013.76

引用次数: 0

Performance Comparison of Speculative Taskloop and OpenMP-for-Loop Thread-Level Speculation on Hardware Transactional Memory 推测型Taskloop和OpenMP-for-Loop在硬件事务性内存上线程级推测的性能比较

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00021

Juan Salamanca

引用次数: 0

[Full] Deep Heuristic for Broadcasting in Arbitrary Networks [完整]基于深度启发式的任意网络广播

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00010

Hovhannes A. Harutyunyan, Narek A. Hovhannisyan, Rakshit Magithiya

引用次数: 0

A type system to avoid runtime errors for Multi-ML 避免Multi-ML运行时错误的类型系统

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00015

F. Gava, V. Allombert, J. Tesson

引用次数: 0

Performance Modeling of Scalable Resource Allocations with the Imperial PEPA Compiler 使用Imperial PEPA编译器对可伸缩资源分配进行性能建模

2022 21st International Symposium on Parallel and Distributed Computing (ISPDC) Pub Date : 2022-07-01 DOI: 10.1109/ISPDC55340.2022.00023

W. Sanders, Srishti Srivastava, I. Banicescu

{"title":"Performance Modeling of Scalable Resource Allocations with the Imperial PEPA Compiler","authors":"W. Sanders, Srishti Srivastava, I. Banicescu","doi":"10.1109/ISPDC55340.2022.00023","DOIUrl":"https://doi.org/10.1109/ISPDC55340.2022.00023","url":null,"abstract":"Advances in computational resources have led to corresponding increases in the scale of large parallel and distributed computer (PDC) systems. With these increases in scale, it becomes increasingly important to understand how these systems will perform as they scale when they are planned and defined, rather than post deployment. Modeling and simulation of these systems can be used to identify unexpected problems and bottlenecks, verify operational functionality, and can result in significant cost savings and avoidance if done prior to the often large capital expenditures that accompany major parallel and distributed computer system deployments. In this paper, we evaluate how PDC systems perform while they are subject to increases in both the number of applications and the number of machines. We generate 42,000 models and evaluate them with the Imperial PEPA Compiler to determine the scaling effects across both an increasing number of applications and an increasing number of machines. These results are then utilized to develop a heuristic for predicting the makespan time for sets of applications mapped onto a number of machines where the applications are subjected to perturbations at runtime. While in the current work the estimated application rates and perturbed rates considered are based on the uniform probability distribution, future work will include a wider range of probability distributions for these rates.","PeriodicalId":389334,"journal":{"name":"2022 21st International Symposium on Parallel and Distributed Computing (ISPDC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128244532","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: 0