Accelerating Video-Mining Applications Using Many Small, General-Purpose Cores
Eric Li, Wenlong Li, Xiaofeng Tong, Jianguo Li, Yurong Chen, Tao Wang, Patricia P. Wang, Wei Hu, Yangzhou Du, Yimin Zhang, Yen-Kuang Chen · IEEE Micro · 2008
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 19times to 62times from 64 cores and get an extra 2.3times speedup from 128-bit SIMD vectorization on the proposed architecture.