Improving Bit Flip Reduction for Biased and Random Data

Nonvolatile memory technologies such as Spin-Transfer Torque Random Access Memory (STT-RAM) and Phase Change Memory (PCM) are emerging as promising replacements to DRAM. Before deploying STT-RAM and PCM into functional systems, a number of challenges still remain must be addressed. Specifically, both require relatively high write energy, STT-RAM suffers from high bit error rates and PCM suffers from low endurance. A common solution to overcome those challenges is to minimize the number of bits changed per write. In this paper, we propose and evaluate the hybrid coset encoder to efficiently improve and balance the bit flip reduction for biased and unbiased data. The main core of the coset encoder consists of biased and unbiased vectors which maps the data input to a larger set of data vectors. Subsequently, the intermediate data vector that yields the least number of differences when compared to the currently stored data is selected. Our evaluation shows that hybrid coset encoder reduces bit flips by up to 25 percent over a baseline differential writing scheme. Further, our proposed scheme reduces bit flips by up to 20 percent over the leading bit-flip minimization scheme for biased data, while achieving very low decoding overhead similar to the Flip-N-Write scheme.