{"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":"1 1","pages":"0"},"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\":\"1 1\",\"pages\":\"0\"},\"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}
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.