期刊
IEEE TRANSACTIONS ON ELECTRON DEVICES
卷 65, 期 10, 页码 4304-4312出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TED.2018.2865352
关键词
Approximate message passing (AMP); compressed sensing (CS); in-memory computing; phase-change memory (PCM)
资金
- European Research Council through the European Union's Horizon 2020 Research and Innovation Program [682675]
- European Union's Horizon 2020 Research and Innovation Program through the project MNEMOSENE [780215]
In-memory computing is a promising non-von Neumann approach where certain computational tasks are performed within resistive memory units by exploiting their physical attributes. In this paper, we propose a new method for fast and robust compressed sensing (CS) of sparse signals with approximate message passing recovery using in-memory computing. The measurement matrix for CS is encoded in the conductance states of resistive memory devices organized in a crossbar array. In this way, the matrix-vector multiplications associated with both the compression and recovery tasks can be performed by the same crossbar array without intermediate data movements at potential O(1) time complexity. For a signal of size N, the proposed method achieves a potential O(N)-fold recovery complexity reduction compared with a standard software approach. We show the array-level robustness of the scheme through large-scale experimental demonstrations using more than 256k phase-change memory devices.
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