GO:大型不规则图的out - core Partitioning

Gurneet Kaur, Rajesh K. Gupta
{"title":"GO:大型不规则图的out - core Partitioning","authors":"Gurneet Kaur, Rajesh K. Gupta","doi":"10.1109/nas51552.2021.9605433","DOIUrl":null,"url":null,"abstract":"Single-PC, disk-based processing of large irregular graphs has recently gained much popularity. At the core of a disk-based system is a static graph partitioning that must be created before the processing starts. By handling one partition at a time, graphs that do not fit in memory are processed on a single machine. However, the multilevel graph partitioning algorithms used by the most sophisticated partitioners cannot be run on the same machine as their memory requirements far exceed the size of the graph. The popular memory efficient Mt-Metis graph partitioner requires 4.8× to 13.8× the memory needed to hold the entire graph in memory. To overcome this problem, we present the GO out-of-core graph partitioner that can successfully partition large graphs on a single machine. GO performs just two passes over the entire input graph, partition creation pass that creates balanced partitions and partition refinement pass that reduces edgecuts. Both passes function in a memory constrained manner via disk-based processing. GO successfully partitions large graphs for which Mt-Metis runs out of memory. For graphs that can be successfully partitioned by Mt-Metis on a single machine, GO produces balanced 8-way partitions with 11.8× to 76.2× fewer edgecuts using 1.9× to 8.3× less memory in comparable runtime.","PeriodicalId":135930,"journal":{"name":"2021 IEEE International Conference on Networking, Architecture and Storage (NAS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"GO: Out-Of-Core Partitioning of Large Irregular Graphs\",\"authors\":\"Gurneet Kaur, Rajesh K. Gupta\",\"doi\":\"10.1109/nas51552.2021.9605433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Single-PC, disk-based processing of large irregular graphs has recently gained much popularity. At the core of a disk-based system is a static graph partitioning that must be created before the processing starts. By handling one partition at a time, graphs that do not fit in memory are processed on a single machine. However, the multilevel graph partitioning algorithms used by the most sophisticated partitioners cannot be run on the same machine as their memory requirements far exceed the size of the graph. The popular memory efficient Mt-Metis graph partitioner requires 4.8× to 13.8× the memory needed to hold the entire graph in memory. To overcome this problem, we present the GO out-of-core graph partitioner that can successfully partition large graphs on a single machine. GO performs just two passes over the entire input graph, partition creation pass that creates balanced partitions and partition refinement pass that reduces edgecuts. Both passes function in a memory constrained manner via disk-based processing. GO successfully partitions large graphs for which Mt-Metis runs out of memory. For graphs that can be successfully partitioned by Mt-Metis on a single machine, GO produces balanced 8-way partitions with 11.8× to 76.2× fewer edgecuts using 1.9× to 8.3× less memory in comparable runtime.\",\"PeriodicalId\":135930,\"journal\":{\"name\":\"2021 IEEE International Conference on Networking, Architecture and Storage (NAS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Networking, Architecture and Storage (NAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/nas51552.2021.9605433\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Networking, Architecture and Storage (NAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/nas51552.2021.9605433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

单pc、基于磁盘的大型不规则图形处理最近得到了广泛的普及。基于磁盘的系统的核心是静态图分区,必须在处理开始之前创建它。通过一次处理一个分区,在一台机器上处理不适合内存的图。然而,最复杂的分区器所使用的多层图分区算法不能在同一台机器上运行,因为它们的内存需求远远超过图的大小。流行的内存高效的Mt-Metis图分区器需要4.8到13.8倍的内存才能将整个图保存在内存中。为了克服这个问题,我们提出了GO out- core图分区器,它可以在单个机器上成功地对大型图进行分区。GO只在整个输入图上执行两次传递:创建平衡分区的分区创建传递和减少切边的分区细化传递。两者都通过基于磁盘的处理以内存受限的方式传递函数。GO成功地对Mt-Metis耗尽内存的大型图进行分区。对于可以通过Mt-Metis在单个机器上成功分区的图,GO产生平衡的8路分区,在可比运行时使用1.9到8.3倍的内存,减少了11.8到76.2倍的切边。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
GO: Out-Of-Core Partitioning of Large Irregular Graphs
Single-PC, disk-based processing of large irregular graphs has recently gained much popularity. At the core of a disk-based system is a static graph partitioning that must be created before the processing starts. By handling one partition at a time, graphs that do not fit in memory are processed on a single machine. However, the multilevel graph partitioning algorithms used by the most sophisticated partitioners cannot be run on the same machine as their memory requirements far exceed the size of the graph. The popular memory efficient Mt-Metis graph partitioner requires 4.8× to 13.8× the memory needed to hold the entire graph in memory. To overcome this problem, we present the GO out-of-core graph partitioner that can successfully partition large graphs on a single machine. GO performs just two passes over the entire input graph, partition creation pass that creates balanced partitions and partition refinement pass that reduces edgecuts. Both passes function in a memory constrained manner via disk-based processing. GO successfully partitions large graphs for which Mt-Metis runs out of memory. For graphs that can be successfully partitioned by Mt-Metis on a single machine, GO produces balanced 8-way partitions with 11.8× to 76.2× fewer edgecuts using 1.9× to 8.3× less memory in comparable runtime.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
NVSwap: Latency-Aware Paging using Non-Volatile Main Memory Deflection-Aware Routing Algorithm in Network on Chip against Soft Errors and Crosstalk Faults PLMC: A Predictable Tail Latency Mode Coordinator for Shared NVMe SSD with Multiple Hosts Efficient NVM Crash Consistency by Mitigating Resource Contention Characterizing AI Model Inference Applications Running in the SGX Environment
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1