{"title":"有限大小突发缓冲区的I/O调度部署高性能计算","authors":"Benbo Zha, Hong Shen","doi":"10.1109/PDCAT46702.2019.00021","DOIUrl":null,"url":null,"abstract":"Burst-Buffers is a high throughput, small size intermediate storage system integrated between computing nodes and permanent storage system to mitigate the I/O bottleneck problem in modern High Performance Computing (HPC) platforms. This system, however, is unable to effectively handle variable-intensity I/O bursts resulted by unpredictable concurrent accesses to the shared Parallel File System (PFS). In this paper, we introduce a probabilistic I/O scheduling method that takes into account of the burst-buffer load state and instantaneous I/O load distribution of the system based on the probabilistic model of applications to relieve the I/O congestion when I/O load exceeds the PFS bandwidth caused by dynamic application interference. The proposed scheduling method for limited-size Burst-Buffers deployed HPC platforms makes online decision of probabilistic selection of concurrent I/O requests for going through (to PFS), buffering (to Burst-Buffers) or declination in accordance to both the available I/O bandwidth and the current buffer state in order to maximize system efficiency or minimize application dilation. Extensive experiment results on actual characteristic synthetic data show that our method handles the I/O congestion effectively.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"I/O Scheduling for Limited-Size Burst-Buffers Deployed High Performance Computing\",\"authors\":\"Benbo Zha, Hong Shen\",\"doi\":\"10.1109/PDCAT46702.2019.00021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Burst-Buffers is a high throughput, small size intermediate storage system integrated between computing nodes and permanent storage system to mitigate the I/O bottleneck problem in modern High Performance Computing (HPC) platforms. This system, however, is unable to effectively handle variable-intensity I/O bursts resulted by unpredictable concurrent accesses to the shared Parallel File System (PFS). In this paper, we introduce a probabilistic I/O scheduling method that takes into account of the burst-buffer load state and instantaneous I/O load distribution of the system based on the probabilistic model of applications to relieve the I/O congestion when I/O load exceeds the PFS bandwidth caused by dynamic application interference. The proposed scheduling method for limited-size Burst-Buffers deployed HPC platforms makes online decision of probabilistic selection of concurrent I/O requests for going through (to PFS), buffering (to Burst-Buffers) or declination in accordance to both the available I/O bandwidth and the current buffer state in order to maximize system efficiency or minimize application dilation. Extensive experiment results on actual characteristic synthetic data show that our method handles the I/O congestion effectively.\",\"PeriodicalId\":166126,\"journal\":{\"name\":\"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDCAT46702.2019.00021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDCAT46702.2019.00021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
I/O Scheduling for Limited-Size Burst-Buffers Deployed High Performance Computing
Burst-Buffers is a high throughput, small size intermediate storage system integrated between computing nodes and permanent storage system to mitigate the I/O bottleneck problem in modern High Performance Computing (HPC) platforms. This system, however, is unable to effectively handle variable-intensity I/O bursts resulted by unpredictable concurrent accesses to the shared Parallel File System (PFS). In this paper, we introduce a probabilistic I/O scheduling method that takes into account of the burst-buffer load state and instantaneous I/O load distribution of the system based on the probabilistic model of applications to relieve the I/O congestion when I/O load exceeds the PFS bandwidth caused by dynamic application interference. The proposed scheduling method for limited-size Burst-Buffers deployed HPC platforms makes online decision of probabilistic selection of concurrent I/O requests for going through (to PFS), buffering (to Burst-Buffers) or declination in accordance to both the available I/O bandwidth and the current buffer state in order to maximize system efficiency or minimize application dilation. Extensive experiment results on actual characteristic synthetic data show that our method handles the I/O congestion effectively.