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VLSI systems in the nanometer regime suffer from high defect rates and large parametric variations that lead to yield loss as well as reduced reliability of operation. In this paper, we propose a novel memory-based computation framework that exploits on-chip memory for reliable operation by transferring activity from a defective or unreliable functional unit to the embedded memory. This allows the die to run at a reduced performance level instead of being completely discarded or being throttled (in case of variations). We show that the proposed method improves yield and reliability in a superscalar out-of-order processor by tolerating defective functional units and allowing dynamic thermal management. The simulation results show that it entails only a small loss in performance (average 1.8%) at the cost of 9.5% of area overhead required with hardware duplication.