Name
Abstract | ||
|---|---|---|
Connected mobile applications, known as the Internet of Things (IoT), require deploying extensive efforts to optimize power consumption and to improve the system performance at the same time. One way to reach this target is based on sacrificing the computing precision adopting different approximate computing methodologies for boosting system performance and reducing the power consumption. In this work, Approximate Precision Computing (APC) based on redundant and on-line arithmetic operators is introduced. It provides the possibility to adapt the computing precision at will, depending on the performance and/or power requirements of the application. The proposed approach supplies an efficient power and area optimized solution with higher performance and without compromising the computing precision. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/DTIS.2019.8735067 | 2019 14th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS) |
Keywords | Field | DocType |
Adders,Power demand,Approximate computing,Delays,Shift registers,Internet of Things | Shift register,Adder,Computer science,Internet of Things,Electronic engineering,Power demand,Boosting (machine learning),Computer engineering,Arithmetic operators,Power consumption,Approximate computing | Conference |
ISBN | Citations | PageRank |
978-1-7281-3424-6 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Skaf | 1 | 13 | 3.57 |
| Mona Ezzadeen | 2 | 0 | 0.34 |
| Benabdenbi, M. | 3 | 0 | 0.68 |
| Laurent Fesquet | 4 | 289 | 49.04 |