Abstract
Conventional low-power static random access memories (SRAMs) reduce read energy by decreasing the bit-line voltage swings uniformly across the bit-line columns. This is because the read energy is proportional to the bit-line swings. On the other hand, bit-line swings are limited by the need to avoid decision errors especially in the most significant bits. We propose a principled approach to determine optimal non-uniform bit-line swings by formulating convex optimization problems. For a given constraint on mean squared error of retrieved words, we consider criteria to minimize energy (for low-power SRAMs), maximize speed (for high-speed SRAMs), and minimize energy-delay product. These optimization problems can be interpreted as classical water-filling, ground-flattening and water-filling, and sand-pouring and water-filling, respectively. By leveraging these interpretations, we also propose greedy algorithms to obtain optimized discrete swings. Numerical results show that energy-optimal swing assignment reduces energy consumption by half at a peak signal-to-noise ratio of 30 dB for an 8-bit accessed word. The energy savings increase to four times for a 16-bit accessed word.
Original language | English (US) |
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Article number | 8368137 |
Pages (from-to) | 4826-4841 |
Number of pages | 16 |
Journal | IEEE Transactions on Communications |
Volume | 66 |
Issue number | 10 |
DOIs | |
State | Published - Oct 2018 |
Keywords
- Static random access memory (SRAM)
- convex optimization
- discrete optimization
- information theory
ASJC Scopus subject areas
- Electrical and Electronic Engineering