Hybrid stacked memory architecture for energy efficient embedded chip-multiprocessors based on compiler directed approach
2015 6th International Green and Sustainable Computing Conference
Institute of Electrical and Electronics Engineers Inc.
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Energy consumption becomes the most critical limitation on the performance of nowadays embedded system designs. On-chip memories due to major contribution in overall system energy consumption are always significant issue for embedded systems. Using conventional memory technologies in future designs in nano-scale era causes a drastic increase in leakage power consumption and temperature-related problems. Emerging non-volatile memory (NVM) technologies are promising replacement for conventional memory structure in embedded systems due to its attractive characteristics such as near-zero leakage power, high density and non-volatility. Recent advantages of NVM technologies can significantly mitigate the issue of memory leakage power. However, they introduce new challenges such as limited write endurance and high write energy consumption which restrict them for adoption in modern memory systems. In this article, we propose a stacked hybrid memory system to minimize energy consumption for 3D embedded chip-multiprocessors (eCMP). For reaching this target, we present a convex optimization-based model to distribute data blocks between SRAM and NVM banks based on data access pattern derived by compiler. Our compiler-assisted hybrid memory architecture can achieve up to 51.28 times improvement in lifetime. In addition, experimental results show that our proposed method reduce energy consumption by 56% on average compared to the traditional memory design where single technology is used. © 2015 IEEE.
Convex-optimization based model
Embedded chip-multiprocessor (eCMP)
Hybrid memory architecture
Non-volatile memory (NVM)
Data storage equipment
Static random access storage
Data access patterns
Emerging non-volatile memory
Leakage power consumption
Reduce energy consumption
System energy consumption
Published Version (Please cite this version)http://dx.doi.org/10.1109/IGCC.2015.7393714
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