TY - GEN
T1 - Optimizing the Write Fidelity of MRAMs
AU - Kim, Yongjune
AU - Jeon, Yoocharn
AU - Guyot, Cyril
AU - Cassuto, Yuval
N1 - Publisher Copyright: © 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs significant write-energy costs, which should be reduced for the large-scale deployment of MRAMs. In this paper, we formulate an optimization problem to maximize the memory fidelity given energy constraints, and propose a biconvex optimization approach to solve it. The basic idea is to allocate non-uniform write pulses depending on the importance of each bit position. We consider the mean squared error (MSE) as a fidelity metric and propose an iterative water-filling algorithm to minimize the MSE. Although the iterative algorithm does not guarantee the global optimality, we can choose a proper starting point that decreases the MSE exponentially and guarantees fast convergence. For an 8-bit accessed word, the proposed algorithm reduces the MSE by a factor of 21.
AB - Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs significant write-energy costs, which should be reduced for the large-scale deployment of MRAMs. In this paper, we formulate an optimization problem to maximize the memory fidelity given energy constraints, and propose a biconvex optimization approach to solve it. The basic idea is to allocate non-uniform write pulses depending on the importance of each bit position. We consider the mean squared error (MSE) as a fidelity metric and propose an iterative water-filling algorithm to minimize the MSE. Although the iterative algorithm does not guarantee the global optimality, we can choose a proper starting point that decreases the MSE exponentially and guarantees fast convergence. For an 8-bit accessed word, the proposed algorithm reduces the MSE by a factor of 21.
UR - http://www.scopus.com/inward/record.url?scp=85090413944&partnerID=8YFLogxK
U2 - 10.1109/ISIT44484.2020.9173990
DO - 10.1109/ISIT44484.2020.9173990
M3 - منشور من مؤتمر
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 792
EP - 797
BT - 2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
T2 - 2020 IEEE International Symposium on Information Theory, ISIT 2020
Y2 - 21 July 2020 through 26 July 2020
ER -