Accelerating Video-Mining Applications Using Many Small, General-Purpose Cores

Authors:
Eric Li;Wenlong Li;Xiaofeng Tong;Jianguo Li;Yurong Chen;Tao Wang;Patricia P. Wang;Wei Hu;Yangzhou Du;Yimin Zhang;Yen-Kuang Chen
Affiliations:
Intel;Intel;Intel;Intel;Intel;Intel;Intel;Intel;Intel;Intel;Intel
Venue:
IEEE Micro
Year:
2008

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Abstract

Emerging video-mining applications such as image and video retrieval and indexing will require real-time processing capabilities. A many-core architecture with 64 small, in-order, general-purpose cores as the accelerator can help meet the necessary performance goals and requirements. The key video-mining modules can achieve parallel speedups of 19× to 62× from 64 cores and get an extra 2.3× speedup from 128-bit SIMD vectorization on the proposed architecture.