Exploring Approximate Memory for Energy-Efficient Computing
Author:
Affiliation:
1. Yarmouk University,Computer Engineering Department,Irbid,Jordan
2. AlShrouk Trading Company, Najran University,Najran,Saudi Arabia,61441
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10459226/10459347/10459495.pdf?arnumber=10459495
Reference22 articles.
1. Machine-Learning-Based Self-Tunable Design of Approximate Computing
2. Highly-Reliable Approximate Quadruple Modular Redundancy with Approximation-Aware Voting
3. Comparative Study of Approximate Multipliers
4. A Quality-assured Approximate Hardware Accelerators–based on Machine Learning and Dynamic Partial Reconfiguration
5. Low Power-Area based Composite 6T-8T SRAM for soft computing applications
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