An FPGA-based In-NIC Cache Approach for Lazy Learning Outlier Filtering

Ami Hayashi, Hiroki Matsutani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

As data sets grow rapidly in size and the number, an outlier detection that filters unnecessary normal information becomes important. In this paper, we propose to move the outlier detection from an application layer to a NIC (Network Interface Card). Only anomalous items or events are delivered for a network protocol stack and the other packets are discarded at the NIC. The demands for storage and computation costs at a host are thus drastically reduced. We employ lazy learning algorithms for the outlier detection, because they can be applied to complex reference data including different clusters. However, it is challenging to offload the lazy learning to NIC hardware because of high computational cost and huge reference data. In this paper, we propose to cache only a frequently-Accessed portion of reference data in the NIC. This idea can be applied to lazy learning algorithms in general. LOF (Local Outlier Factor) and KNN (K-Nearest Neighbor) are thus implemented on an FPGA (Field Programmable Gate Arrays) based NIC. Simulation results of the proposed system using LOF with 100,000 reference data show that 45% to 90% of queries are hit to the proposed cache and filtered at the NIC. The results are corresponding to 1.82x to 10x throughput improvements on the outlier filtering compared to that of a software-based execution.

Original languageEnglish
Title of host publicationProceedings - 2017 25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages15-22
Number of pages8
ISBN (Electronic)9781509060580
DOIs
Publication statusPublished - 2017 Apr 26
Event25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2017 - St. Petersburg, Russian Federation
Duration: 2017 Mar 62017 Mar 8

Other

Other25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2017
CountryRussian Federation
CitySt. Petersburg
Period17/3/617/3/8

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Keywords

  • FPGA NIC
  • K Nearest Neighbor
  • Lazy Learning
  • Local Outlier Factor
  • Outlier Detection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

Cite this

Hayashi, A., & Matsutani, H. (2017). An FPGA-based In-NIC Cache Approach for Lazy Learning Outlier Filtering. In Proceedings - 2017 25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2017 (pp. 15-22). [7912620] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PDP.2017.48