Koushanfar, Farinaz2012-09-062012-09-062012-09-062012-09-062012-052012-09-05May 2012Mirhoseini, Azalia. "Coding for Phase Change Memory Performance Optimization." (2012) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/64682">https://hdl.handle.net/1911/64682</a>.https://hdl.handle.net/1911/64682Over the past several decades, memory technologies have exploited continual scaling of CMOS to drastically improve performance and cost. Unfortunately, charge-based memories become unreliable beyond 20 nm feature sizes. A promising alternative is Phase-Change-Memory (PCM) which leverages scalable resistive thermal mechanisms. To realize PCM's potential, a number of challenges, including the limited wear-endurance and costly writes, need to be addressed. This thesis introduces novel methodologies for encoding data on PCM which exploit asymmetries in read/write performance to minimize memory's wear/energy consumption. First, we map the problem to a distance-based graph clustering problem and prove it is NP-hard. Next, we propose two different approaches: an optimal solution based on Integer-Linear-Programming, and an approximately-optimal solution based on Dynamic-Programming. Our methods target both single-level and multi-level cell PCM and provide further optimizations for stochastically-distributed data. We devise a low overhead hardware architecture for the encoder. Evaluations demonstrate significant performance gains of our framework.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Phase change memoryCodingEnergy optimizationThesis2012-09-06123456789/ETD-2012-05-151