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IDIO: Orchestrating Inbound Network Data on Server Processors

Title
IDIO: Orchestrating Inbound Network Data on Server Processors
Authors
Alian, MohammadShin, JongminKang, Ki DongWang, RenDaglis, AlexandrosKim, DaehoonKim, Nam Sung
DGIST Authors
Alian, Mohammad; Shin, Jongmin; Kang, Ki Dong; Wang, Ren; Daglis, Alexandros; Kim, Daehoon; Kim, Nam Sung
Issue Date
2021-01
Citation
IEEE Computer Architecture Letters, 20(1), 30-33
Type
Article
Article Type
Article
Author Keywords
CacheNetworkData Direct I/ODatacenters
Keywords
BandwidthRandom access memoryServersInterferenceProgram processorsNoise measurementPerformance evaluation
ISSN
1556-6056
Abstract
Network bandwidth demand in datacenters is doubling every 12 to 15 months. In response to this demand, high-bandwidth network interface cards, each capable of transferring 100s of Gigabits of data per second, are making inroads into the servers of next-generation datacenters. Such unprecedented data delivery rates on server endpoints raise new challenges, as inbound network traffic placement decisions within the memory hierarchy have a direct impact on end-to-end performance. Modern server-class Intel processors leverage DDIO technology to steer all inbound network data into the last-level cache (LLC), regardless of the network traffic's nature. This static data placement policy is suboptimal, both from a performance and an energy efficiency standpoint. In this work, we design IDIO, a framework that-unlike DDIO-dynamically decides where to place inbound network traffic within a server's multi-level memory hierarchy. IDIO dynamically monitors system behavior and distinguishes between different traffic classes to determine and periodically re-evaluate the best placement location for each flow: LLC, mid-level (L2) cache or DRAM. Our results show that IDIO increases a server's maximum sustainable load by up to ˜33.3% across various network functions. IEEE
URI
http://hdl.handle.net/20.500.11750/12636
DOI
10.1109/lca.2020.3044923
Publisher
Institute of Electrical and Electronics Engineers
Related Researcher
  • Author Kim, Daehoon Computer Architecture and Systems Lab
  • Research Interests Computer Architecture and Systems; Virtualization; Cloud Computing
Files:
There are no files associated with this item.
Collection:
Department of Electrical Engineering and Computer ScienceComputer Architecture and Systems Lab1. Journal Articles


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