A comparison of full and partial predicated execution support for ILP processors
ISCA '95 Proceedings of the 22nd annual international symposium on Computer architecture
Proceedings of the 34th annual ACM/IEEE international symposium on Microarchitecture
DSD '02 Proceedings of the Euromicro Symposium on Digital Systems Design
Superword-Level Parallelism in the Presence of Control Flow
Proceedings of the international symposium on Code generation and optimization
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Proceedings of the 2006 international symposium on Low power electronics and design
Proceedings of the conference on Design, automation and test in Europe
Energy-Aware Interconnect Optimization for a Coarse Grained Reconfigurable Processor
VLSID '08 Proceedings of the 21st International Conference on VLSI Design
Compiling control-intensive loops for CGRAs with state-based full predication
Proceedings of the Conference on Design, Automation and Test in Europe
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It has been one of the most fundamental challenges in architecture design to achieve high performance with low power while maintaining flexibility. Parallel architectures such as coarse-grained reconfigurable architecture, where multiple PEs are tightly coupled with each other, can be a viable solution to the problem. However, the PEs are typically controlled by a centralized control unit, which makes it hard to parallelize programs requiring different control of each PE. To overcome this limitation, it is essential to convert control flows into data flows by adopting the predicated execution technique, but it may incur additional power consumption. This paper reveals power issues in the predicated execution and proposes a novel technique to mitigate power overhead of predicated execution. Contrary to the conventional approach, the proposed mechanism can decide whether to suppress instruction execution or not without decoding the instructions and does not require additional instruction bits, thereby resulting in energy savings. Experimental results show that energy consumed by the reconfigurable array and its configuration memory is reduced by up to 23.9%.