Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM
Yoshinori Ono, Kimiyoshi Usami
A non-volatile memory (NVM) employing MTJ has a lot of strong points such as read/write performance, best endurance and operating-voltage compatibility with standard CMOS. However, it consumes a lot of energy when writing the data. This becomes an obstacle when applying to battery-operated mobile devices. To solve this problem, we propose an approach to augment the capability of the precision scaling technique for the write operation in NVM. Precision scaling is an approximate computing technique to reduce the bit width of data (i.e. precision) for energy reduction. When writing image data to NVM with the precision scaling, the write energy and the image quality are changed according to the write time and the target bit range. We propose an energy-efficient approximate storing scheme for non-volatile flip-flops and a magnetic randomaccess memory (MRAM) that allows us to write the data by optimizing the bit positions to split the data and the write time for each bit range. By using the statistical model, we obtained optimal values for the write time and the targeted bit range under the trade-off between the write energy reduction and image quality degradation. Simulation results have demonstrated that by using these optimal values the write energy can be reduced up to 50% while maintaining the acceptable image quality. We also investigated the relationship between the input images and the output image quality when using this approach in detail. In addition, we evaluated the energy benefits when applying our approach to nine types of image processing including linear filters and edge detectors. Results showed that the write energy is reduced by further 12.5% at the maximum.
IEICE Transactions on Electronics
https://doi.org/10.1587/transele.2020CDP0009
approximate computing
magnetic tunnel junction
write energy
10.1587/transele.2020CDP0009
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Flip flop circuits Engineering & Materials Science 100%
Image quality Engineering & Materials Science 63%
Data storage equipment Engineering & Materials Science 52%
Energy Chemical Compounds 40%
Statistical Models Engineering & Materials Science 15%
Mobile computing Engineering & Materials Science 14%
Durability Engineering & Materials Science 13%
Image processing Engineering & Materials Science 13%
Ono, Y., & Usami, K. (2021). Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM. IEICE Transactions on Electronics, (7), 338-349. https://doi.org/10.1587/transele.2020CDP0009
Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM. / Ono, Yoshinori; Usami, Kimiyoshi.
In: IEICE Transactions on Electronics, No. 7, 01.07.2021, p. 338-349.
Ono, Y & Usami, K 2021, 'Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM', IEICE Transactions on Electronics, no. 7, pp. 338-349. https://doi.org/10.1587/transele.2020CDP0009
Ono Y, Usami K. Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM. IEICE Transactions on Electronics. 2021 Jul 1;(7):338-349. https://doi.org/10.1587/transele.2020CDP0009
Ono, Yoshinori ; Usami, Kimiyoshi. / Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM. In: IEICE Transactions on Electronics. 2021 ; No. 7. pp. 338-349.
@article{6318ff41c5fd4636a57afa676896d94f,
title = "Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM",
abstract = "A non-volatile memory (NVM) employing MTJ has a lot of strong points such as read/write performance, best endurance and operating-voltage compatibility with standard CMOS. However, it consumes a lot of energy when writing the data. This becomes an obstacle when applying to battery-operated mobile devices. To solve this problem, we propose an approach to augment the capability of the precision scaling technique for the write operation in NVM. Precision scaling is an approximate computing technique to reduce the bit width of data (i.e. precision) for energy reduction. When writing image data to NVM with the precision scaling, the write energy and the image quality are changed according to the write time and the target bit range. We propose an energy-efficient approximate storing scheme for non-volatile flip-flops and a magnetic randomaccess memory (MRAM) that allows us to write the data by optimizing the bit positions to split the data and the write time for each bit range. By using the statistical model, we obtained optimal values for the write time and the targeted bit range under the trade-off between the write energy reduction and image quality degradation. Simulation results have demonstrated that by using these optimal values the write energy can be reduced up to 50% while maintaining the acceptable image quality. We also investigated the relationship between the input images and the output image quality when using this approach in detail. In addition, we evaluated the energy benefits when applying our approach to nine types of image processing including linear filters and edge detectors. Results showed that the write energy is reduced by further 12.5% at the maximum.",
keywords = "approximate computing, image data, image quality, magnetic tunnel junction, non-volatile memory, write energy",
author = "Yoshinori Ono and Kimiyoshi Usami",
note = "Funding Information: This work was supported by SIT Research Center for Green Innovation. This work was also supported through the activities of VDEC, The University of Tokyo, in collaboration with Synopsys, Inc. Publisher Copyright: {\textcopyright} 2021 Institute of Electronics, Information and Communication, Engineers, IEICE. All rights reserved.",
doi = "10.1587/transele.2020CDP0009",
journal = "IEICE Transactions on Electronics",
publisher = "Maruzen Co., Ltd/Maruzen Kabushikikaisha",
T1 - Energy Efficient Approximate Storing of Image Data for MTJ Based Non-Volatile Flip-Flops and MRAM
AU - Ono, Yoshinori
AU - Usami, Kimiyoshi
N1 - Funding Information: This work was supported by SIT Research Center for Green Innovation. This work was also supported through the activities of VDEC, The University of Tokyo, in collaboration with Synopsys, Inc. Publisher Copyright: © 2021 Institute of Electronics, Information and Communication, Engineers, IEICE. All rights reserved.
N2 - A non-volatile memory (NVM) employing MTJ has a lot of strong points such as read/write performance, best endurance and operating-voltage compatibility with standard CMOS. However, it consumes a lot of energy when writing the data. This becomes an obstacle when applying to battery-operated mobile devices. To solve this problem, we propose an approach to augment the capability of the precision scaling technique for the write operation in NVM. Precision scaling is an approximate computing technique to reduce the bit width of data (i.e. precision) for energy reduction. When writing image data to NVM with the precision scaling, the write energy and the image quality are changed according to the write time and the target bit range. We propose an energy-efficient approximate storing scheme for non-volatile flip-flops and a magnetic randomaccess memory (MRAM) that allows us to write the data by optimizing the bit positions to split the data and the write time for each bit range. By using the statistical model, we obtained optimal values for the write time and the targeted bit range under the trade-off between the write energy reduction and image quality degradation. Simulation results have demonstrated that by using these optimal values the write energy can be reduced up to 50% while maintaining the acceptable image quality. We also investigated the relationship between the input images and the output image quality when using this approach in detail. In addition, we evaluated the energy benefits when applying our approach to nine types of image processing including linear filters and edge detectors. Results showed that the write energy is reduced by further 12.5% at the maximum.
AB - A non-volatile memory (NVM) employing MTJ has a lot of strong points such as read/write performance, best endurance and operating-voltage compatibility with standard CMOS. However, it consumes a lot of energy when writing the data. This becomes an obstacle when applying to battery-operated mobile devices. To solve this problem, we propose an approach to augment the capability of the precision scaling technique for the write operation in NVM. Precision scaling is an approximate computing technique to reduce the bit width of data (i.e. precision) for energy reduction. When writing image data to NVM with the precision scaling, the write energy and the image quality are changed according to the write time and the target bit range. We propose an energy-efficient approximate storing scheme for non-volatile flip-flops and a magnetic randomaccess memory (MRAM) that allows us to write the data by optimizing the bit positions to split the data and the write time for each bit range. By using the statistical model, we obtained optimal values for the write time and the targeted bit range under the trade-off between the write energy reduction and image quality degradation. Simulation results have demonstrated that by using these optimal values the write energy can be reduced up to 50% while maintaining the acceptable image quality. We also investigated the relationship between the input images and the output image quality when using this approach in detail. In addition, we evaluated the energy benefits when applying our approach to nine types of image processing including linear filters and edge detectors. Results showed that the write energy is reduced by further 12.5% at the maximum.
KW - approximate computing
KW - image data
KW - image quality
KW - magnetic tunnel junction
KW - non-volatile memory
KW - write energy
U2 - 10.1587/transele.2020CDP0009
DO - 10.1587/transele.2020CDP0009
JO - IEICE Transactions on Electronics
JF - IEICE Transactions on Electronics