Abstract
In the conventional computing systems, high redundancy in terms of energy consumption, speed and area are usually applied to guarantee accurate operations. However, energy consumption has become a bottleneck for further scaling down of silicon-based devices, which can no longer be increased to ensure accuracy. In order to find a balance between accuracy and other performance metrics, approximate computing has been intensively studied and applied in the applications that are intrinsically fault tolerant. Featured with non-volatility, fast access speed, high scalability and current-induced thresholding operation, spintronic devices are promising candidates for approximate computing. This chapter exploits the application of approximate techniques in the spintronic device-based circuit designs for energy-efficient processing in-memory. Approximate techniques based on spintronic devices are explored for both traditional full adders and write-only bitwise full adders with reduced complexity. The simulation results show that the energy can be significantly reduced with negligible loss in output quality.
| Original language | English |
|---|---|
| Title of host publication | Approximate Computing |
| Publisher | Springer International Publishing |
| Pages | 99-117 |
| Number of pages | 19 |
| ISBN (Electronic) | 9783030983475 |
| ISBN (Print) | 9783030983468 |
| DOIs | |
| State | Published - 1 Jan 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Accuracy tradeoff
- Approximate computing
- Design complexity reduction
- Error distance
- Fault tolerant
- Full adder
- High energy efficiency
- In memory computing
- Low power
- Magnetic tunnel junction
- Non-volatile memory
- Process variation
- Spin orbit torque
- Spintronic
- Stochastic switching
- Voltage controlled magnetic anisotropy
- Voltage over scaling
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