{"title":"NetFC:在可编程交换机上实现精确浮点运算","authors":"Penglai Cui, H. Pan, Zhenyu Li, Jiaoren Wu, Shengzhuo Zhang, Xingwu Yang, Hongtao Guan, Gaogang Xie","doi":"10.1109/ICNP52444.2021.9651946","DOIUrl":null,"url":null,"abstract":"Programmable switches are recently used for accelerating data-intensive distributed applications. Some computational tasks, traditionally performed on servers in data centers, are offloaded to the network on programmable switches. These tasks may require the support of on-the-fly floatingpoint operations. Unfortunately, the computational capacity of programmable switches is limited to simple integer arithmetic operations. To address this issue, prior approaches either adopt a float-to-integer method or rely on local CPUs of switches, incurring accuracy loss and delayed processing.To this end, we propose NetFC, a table-lookup method to achieve on-the-fly in-network floating-point arithmetic operations nearly without accuracy loss. NetFC adopts a divide-and-conquer mechanism that converts the original huge table into several much smaller tables that are operated by the built-in integer operations. NetFC further leverages a scaling-factor mechanism for improving computational accuracy, and a prefix-based lossless table compression method to reduce memory consumption. We use both synthetic and real-life datasets to evaluate NetFC. The experimental results show that the average accuracy of NetFC is above 99.94% with only 448KB memory consumption. Furthermore, we integrate NetFC into Sonata [12] for detecting Slowloris attack, yielding significant decrease of detection delay.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"NetFC: Enabling Accurate Floating-point Arithmetic on Programmable Switches\",\"authors\":\"Penglai Cui, H. Pan, Zhenyu Li, Jiaoren Wu, Shengzhuo Zhang, Xingwu Yang, Hongtao Guan, Gaogang Xie\",\"doi\":\"10.1109/ICNP52444.2021.9651946\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Programmable switches are recently used for accelerating data-intensive distributed applications. Some computational tasks, traditionally performed on servers in data centers, are offloaded to the network on programmable switches. These tasks may require the support of on-the-fly floatingpoint operations. Unfortunately, the computational capacity of programmable switches is limited to simple integer arithmetic operations. To address this issue, prior approaches either adopt a float-to-integer method or rely on local CPUs of switches, incurring accuracy loss and delayed processing.To this end, we propose NetFC, a table-lookup method to achieve on-the-fly in-network floating-point arithmetic operations nearly without accuracy loss. NetFC adopts a divide-and-conquer mechanism that converts the original huge table into several much smaller tables that are operated by the built-in integer operations. NetFC further leverages a scaling-factor mechanism for improving computational accuracy, and a prefix-based lossless table compression method to reduce memory consumption. We use both synthetic and real-life datasets to evaluate NetFC. The experimental results show that the average accuracy of NetFC is above 99.94% with only 448KB memory consumption. Furthermore, we integrate NetFC into Sonata [12] for detecting Slowloris attack, yielding significant decrease of detection delay.\",\"PeriodicalId\":343813,\"journal\":{\"name\":\"2021 IEEE 29th International Conference on Network Protocols (ICNP)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 29th International Conference on Network Protocols (ICNP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNP52444.2021.9651946\",\"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 29th International Conference on Network Protocols (ICNP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNP52444.2021.9651946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NetFC: Enabling Accurate Floating-point Arithmetic on Programmable Switches
Programmable switches are recently used for accelerating data-intensive distributed applications. Some computational tasks, traditionally performed on servers in data centers, are offloaded to the network on programmable switches. These tasks may require the support of on-the-fly floatingpoint operations. Unfortunately, the computational capacity of programmable switches is limited to simple integer arithmetic operations. To address this issue, prior approaches either adopt a float-to-integer method or rely on local CPUs of switches, incurring accuracy loss and delayed processing.To this end, we propose NetFC, a table-lookup method to achieve on-the-fly in-network floating-point arithmetic operations nearly without accuracy loss. NetFC adopts a divide-and-conquer mechanism that converts the original huge table into several much smaller tables that are operated by the built-in integer operations. NetFC further leverages a scaling-factor mechanism for improving computational accuracy, and a prefix-based lossless table compression method to reduce memory consumption. We use both synthetic and real-life datasets to evaluate NetFC. The experimental results show that the average accuracy of NetFC is above 99.94% with only 448KB memory consumption. Furthermore, we integrate NetFC into Sonata [12] for detecting Slowloris attack, yielding significant decrease of detection delay.