IEEE - Institute of Electrical and Electronics Engineers, Inc. - 14.4 A 21.5M-query-vectors/s 3.37nJ/vector reconfigurable k-nearest-neighbor accelerator with adaptive precision in 14nm tri-gate CMOS

2016 IEEE International Solid-State Circuits Conference (ISSCC)

Author(s): Himanshu Kaul ; Mark A. Anders ; Sanu K. Mathew ; Gregory Chen ; Sudhir K. Satpathy ; Steven K. Hsu ; Amit Agarwal ; Ram K. Krishnamurthy
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 January 2016
Conference Location: San Francisco, CA, USA
Conference Date: 31 January 2016
Page(s): 260 - 261
ISBN (Electronic): 978-1-4673-9467-3
ISBN (Paper): 978-1-4673-9466-6
ISSN (Electronic): 2376-8606
DOI: 10.1109/ISSCC.2016.7418006
Regular:

Energy-efficient k-nearest-neighbor (kNN) computations are key building blocks for computer vision, classification, and machine-learning workloads [1-3]. Determining distances to high-dimensional... View More

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