AnySP: anytime anywhere anyway signal processing
Proceedings of the 36th annual international symposium on Computer architecture
Register file partitioning and recompilation for register file power reduction
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Enabling large decoded instruction loop caching for energy-aware embedded processors
CASES '10 Proceedings of the 2010 international conference on Compilers, architectures and synthesis for embedded systems
Register file partitioning and compiler support for reducing embedded processor power consumption
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Analyzing the Next Generation Software Defined Radio for Future Architectures
Journal of Signal Processing Systems
DLIC: Decoded loop instructions caching for energy-aware embedded processors
ACM Transactions on Embedded Computing Systems (TECS)
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As embedded processors being widely used in specific application domains, such as communications, multimedia, and networking, the register file has contributed a substantial budget in embedded processor energy consumption due to its long working time for the data intensive computations and the large switching capacitance. It is found that 25% of registers can account for 83% of register file accessing time during many embedded application execution. This fact motivates us to reduce the register file power consumption by partitioning the registers to different regions according to their usage pattern. The most frequently used registers are put in the hot part, and the cold part of register file is rarely accessed. We employ the register file bitline splitting and the drowsy register cell techniques in our design to reduce the overall accessing power of the register file. We propose a novel approach to partition the register file in a way so that the largest power saving can be achieved. We formulate the register file partitioning process into a graph partitioning problem, and apply an effective algorithm to obtain the optimal result. We evaluate our algorithm on MiBench applications, and an average saving of 43.6% in the register file access power consumption over the original non-partitioned register file is achieved for the SimpleScalar PISA system.