Normally-Off Computing and Checkpoint/Rollback for Fast, Low-Power, and Reliable Devices

Sophiane Senni 1 Lionel Torres 1 Pascal Benoit 1 Abdoulaye Gamatié 1 Gilles Sassatelli 1
1 ADAC - ADAptive Computing
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Since the advent of complementary metal oxide semiconductors (CMOS), the number of transistors per die has continued to increase, reaching today several billion transistors. As a result, it has been possible to design and fabricate smart devices able to run at high speed. However, the power consumption of systems-on-chip has significantly increased due to the high density integration and the high leakage power of current CMOS transistors. As a result, the limits of heat dissipation make further improvement in performance difficult. A high level of autonomy for battery-powered devices is a real challenge. To deal with these issues, spin-transfer-torque magnetic random-access memory (STT-MRAM) technology is seen as a promising solution. In addition to its attractive performance features, STT-MRAM can bring nonvolatility to a system to allow full data retention after a complete shutdown while maintaining a fast wake-up time. Considering two 32-bit embedded processors, this letter shows how STT-MRAM can improve energy efficiency and reliability of future embedded systems thanks to normally-off computing and checkpointing/rollback techniques. A detailed analysis is performed to evaluate the cost related to the backup/recovery of the system. Index Terms—Spintronic memory and logic, embedded processor, spin-transfer-torque, magnetic random-access memory.
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Contributor : Sophiane Senni <>
Submitted on : Wednesday, April 18, 2018 - 12:51:08 PM
Last modification on : Thursday, April 11, 2019 - 4:29:46 PM


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Sophiane Senni, Lionel Torres, Pascal Benoit, Abdoulaye Gamatié, Gilles Sassatelli. Normally-Off Computing and Checkpoint/Rollback for Fast, Low-Power, and Reliable Devices. IEEE Magnetics Letters, IEEE, 2017, 8, pp.1-5. ⟨10.1109/LMAG.2017.2712780⟩. ⟨hal-01767897⟩



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