Bhosale, Swapnil, authorPasricha, Sudeep, advisorRoy, Sourajeet, committee memberBohm, Wim, committee member2019-01-072019-01-072018https://hdl.handle.net/10217/193178As the performance gap between CPU and main memory continues to increase, it causes a significant roadblock to exascale computing. Memory performance has not kept up with CPU performance, and is becoming a bottleneck today, particularly due to the advent of data-intensive applications. To accommodate the vast amount of data required by these applications, emerging non-volatile memory technology STTRAM (Spin-Transfer Torque Random Access Memory) is a good candidate to replace or augment SRAM from last-level cache (LLC) memory because of its high capacity, good scalability, and low power consumption. However, its expensive write operations prevent it from becoming a universal memory candidate. In this thesis, we propose an SRAM-STTRAM hybrid last level cache (LLC) architecture that consumes less energy and performs better than SRAM-only and STTRAM-only LLC. We design an algorithm to reduce write operations to the STTRAM region of the hybrid LLC and consequently minimize the write energy of STTRAM. Compared to two prior state-of-the-art techniques, our proposed technique achieves 29.23% and 5.94% total LLC energy savings and 6.863% and 0.407% performance improvement for various SPLASH2 and PARSEC parallel benchmarks.born digitalmasters thesesengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.last level cachenon-volatile memorySTTRAMLLC energycache coherencyperformanceText