Abstract
This paper presents a novel method for estimating the dynamic energy consumption of soft processors in FPGA, using an operand-value-based model at the instruction level. Our energy model contains three components: the instruction base energy, the maximum variation in the instruction energy due to input data, and the impact of one’s density of the operand values during software execution. Using multiple benchmarks, we demonstrate that our model has only 4.7% average error and 12% worst case error compared to the reference post-place-and-route simulations, and is more than twice as accurate as existing instruction-level models.
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References
Bazzaz, M., Salehi, M., Ejlali, A.: An accurate instruction-level energy estimation model and tool for embedded systems. IEEE Trans. On Instrumentation and Measurement 62(7) (2013)
Xilinx Inc, Power Methodology Guide UG786 (2011). http://www.xilinx.com/support/documentation/sw_manuals/xilinx13_1/ug786_PowerMethodology.pdf
Sinha, A., Chandrakasan, A.P.: JouleTrack-a web based tool for software energy profiling. In: Proceedings, Design Automation Conference pp. 220–225 (2001)
Krishnaswamy, A., Gupta, R.: Dynamic coalescing for 16-bit instructions. ACM TECS 2005, 3–37 (2005)
Xilinx Inc, XPower Analyzer (2011). http://www.xilinx.com/products/design_tools/logic_design/verification/xpower.htm
Synopsys Inc. Power Compiler (2012). http://www.synopsys.com/Tools/Implementation/RTLSynthesis/Pages/PowerCompiler.aspx
Weicker, R.P.: Dhrystone: a synthetic systems programming benchmark. Comm. of the ACM 27, 1013–1030 (1984)
Xilinx Inc.: LogiCORE IP, MicroBlaze micro controller system. http://www.xilinx.com/tools/microblaze.htm
Gurumurthi, S., Sivasubramaniam, A., Irwin, M.J., Vijaykrishnan, N., Kandemir, M.: Using complete machine simulation for software power estimation: The SoftWatt approach. HPCA, pp. 141–150 (2002)
Brooks, D., Tiwari, V., Martonosi, M.: Wattch: A framework for architectural-level power analysis and optimizations. ISCA, pp. 83–94 (2000)
Ahmadinia, A., Ahmad, B., Arslan, T.: A state based framework for efficient system-level power estimation of costum reconfigurable cores. In: Proceedings, SOC Conf., pp. 1–4 (2008)
Chen, J., Thiele, L.: Task partitioning and platform synthesis for energy efficiency. In: Proceedings. RTCSA, pp. 393–402 (2009)
Brandolese, C., et al.: Software energy estimation based on statistical characterization of intermediate compilation code. Symposium. Low Power Electronics and Design (ISLPED), pp. 333–338 (2011)
Tiwari, V., Tien-Chien Lee, M.: Power analysis of a 32-bit embedded microcontroller. ASPDAC, pp. 141–148 (1995)
Tien-Chien Lee, M., Tiwari, V., Malik, S., Fujita, M.: Power analysis and minimization techniques for embedded DSP software. IEEE VLSI, (5), pp. 123–135 (1997)
Roy, S., Bhatia, R., Mathur, A.: An accurate energy estimation framework for VLIW processor cores. In: Proceedings. ICCD, pp. 464–469 (2006)
Kim, J., Kang, K., Shim, H., et al.: Fast estimation of software energy consumption using IPI(inter-prefetch interval) energy model. In: VLSI-SoC, pp. 224–229 (2007)
Sailer, P.M., Philip, M., Kaeli, R.: The DLX Instruction Set Architecture Handbook (1st ed.). Morgan Kaufmann Publishers Inc., CA, USA (1996)
Wallace, G.K.: The JPEG still picture compression standard. IEEE Trans. On Consumer Electronics 38, xviii–xxxiv (1992)
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Al-Khatib, Z., Abdi, S. (2015). Operand-Value-Based Modeling of Dynamic Energy Consumption of Soft Processors in FPGA. In: Sano, K., Soudris, D., Hübner, M., Diniz, P. (eds) Applied Reconfigurable Computing. ARC 2015. Lecture Notes in Computer Science(), vol 9040. Springer, Cham. https://doi.org/10.1007/978-3-319-16214-0_6
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DOI: https://doi.org/10.1007/978-3-319-16214-0_6
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