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As technology scales, reducing leakage power and improving reliability of data stored in memory cells is both important and challenging. While lower threshold voltages increase leakage, lower supply voltages and smaller nodal capacitances reduce energy consumption but increase soft errors rates. In this work, we present a comprehensive study of soft error rates on low-power cache design. First, we study the effect of circuit level techniques, used to reduce the leakage energy consumption, on soft error rates. Our results using custom designs show that many of these approaches may increase the soft error rates as compared to a standard 6T SRAM. We also validate the effects of voltage scaling on soft error rate by performing accelerated tests on off-the-shelf SRAM-based chips using a neutron beam source. Next, we study the impact of cache decay and drowsy cache, which are two commonly used architectural-level leakage reduction approaches, on the cache reliability. Our results indicate that the leakage optimization techniques change the reliability of cache memory. More importantly, we demonstrate that there is a tradeoff between optimizing for leakage power and improving the immunity to soft error. We also study the impact of error correcting codes on soft error rates. Based on this study, we propose an adaptive error correcting scheme to reduce the leakage energy consumption and improve reliability.