Delivering on the promise of universal memory for spin-transfer torque RAM (STT-RAM)

Authors:
Anurag Nigam;Clinton W. Smullen, IV;Vidyabhushan Mohan;Eugene Chen;Sudhanva Gurumurthi;Mircea R. Stan
Affiliations:
University of Virginia, Charlottesville, VA, USA;University of Virginia, CHarlottesville, VA, USA;University of Virginia, Charlottesville, VA, USA;Grandis, Milipitas, CA, USA;University of Virginia, Charlottesville, VA, USA;University of Virginia, Charlottesville, VA, USA
Venue:
Proceedings of the 17th IEEE/ACM international symposium on Low-power electronics and design
Year:
2011

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Abstract

Spin-Transfer Torque RAM (STT-RAM) has emerged as a potential candidate for Universal memory. However, there are two challenges to using STT-RAM in memory system design: (1) the intrinsic variation in the storage element, the Magnetic Tunnel Junction (MTJ), and (2) the high write energy. In this paper, we present a physically based thermal noise model for simulating the statistical variations of MTJs. We have implemented it in HSPICE and validated it against analytical results. We demonstrate its use in setting the write pulse width for a given write error rate. We then propose two write-energy reduction techniques. At the device level, we propose the use of a low-MS ferromagnetic material that can reduce the write energy without sacrificing retention time. At the architecture level, we show that Invert Coding provides a 7% average reduction in the total write energy for the SPEC CPU2006 benchmark suite without any performance overhead.