Detail View

IDIO: Orchestrating Inbound Network Data on Server Processors
Citations

WEB OF SCIENCE

Citations

SCOPUS

Metadata Downloads

Title
IDIO: Orchestrating Inbound Network Data on Server Processors
Issued Date
2021-01
Citation
Alian, Mohammad. (2021-01). IDIO: Orchestrating Inbound Network Data on Server Processors. IEEE Computer Architecture Letters, 20(1), 30–33. doi: 10.1109/lca.2020.3044923
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
Show Full Item Record

File Downloads

  • There are no files associated with this item.

공유

qrcode
공유하기

Related Researcher

김대훈
Kim, Daehoon김대훈

Department of Electrical Engineering and Computer Science

read more

Total Views & Downloads