Chang-Hung Tsai, Tung-Yu Wu, S. Hsu, Chia-Ching Chu, Fang-Ju Ku, Ying-Siou Laio, Chih-Lung Chen, W. Wong, Hsie-Chia Chang, Chen-Yi Lee
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A 7.11mJ/Gb/query data-driven machine learning processor (D2MLP) for big data analysis and applications
A data-driven machine learning processor (D2MLP) with MIMD architecture is designed for big data analysis. Adopting the configurable counting engine array with 3-layer dimension merging, the D2MLP processes maximal 1-128/1024 dimensional data with parallel 64/8 queries in learning stage. Implement in 90nm CMOS technology, the D2MLP achieves 219.9x and 8.2x faster processing time than CPU and GPGPU, respectively. In application phase, maximal 22.7k 128-class classifications/s are performed with the learned density model. Operated at 1.0V and 165MHz, the D2MLP demonstrates an energy-efficient solution for learning and classification with 7.11mJ/Gb/query and 2.3μJ/classification, respectively.
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