Title
LVTTL and SSTL IO Standards Based Energy Efficient FSM Design on 16nm Ultrascale plus FPGA
Date Issued
25 September 2020
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Reducing power dissipation of any device at design stage leads to saving of power consumption in the lifetime of the device that eventually results in saving of energy and resources. With the emergence of Green Computing, energy efficiency has become an important criterion in designing any device. In this work, we are going to design an LVTTL and SSTL IO Standards based energy efficient FSM on a 16nm Ultrascale Plus FPGA. Manufacturer of Ultrascale Plus FPGA claims that it consumes half power in comparison to 7 Series (28nm) FPGA. Here, the power consumption of design of FSM for two different IO standards, LVTTL and SSTL is observed at different output loads: 0, 100 and 10000. We compare the power consumptions of the design for LVTTL and SSTL IO standards to find the most energy efficient architecture for our design among the two. At output load 0, there is 36.51% saving in total on chip power consumption, 84.29% saving in dynamic power consumption and 0.59% saving in static power consumption when we migrate our design from LVTTL to SSTL12. At output load 0, there is 36.06% saving in total on chip power consumption, 83.24% saving in dynamic power consumption and 0.59% saving in static power consumption when we migrate our design from LVTTL to SSTL15. In comparison to LVTTL, there is a significantly less power consumption at different output loads when using SSTL12 and SSTL15 IO standards. The designed FSM will be helpful in reducing heat dissipation, overcoming power management challenges and enhancing the energy efficiency of any device.
Start page
501
End page
504
Language
English
OCDE Knowledge area
Ingeniería del Petróleo, (combustibles, aceites), Energía, Combustibles
Ingeniería eléctrica, Ingeniería electrónica
Subjects
Scopus EID
2-s2.0-85096870710
ISBN of the container
9781728193939
Conference
Proceedings - 2020 12th International Conference on Computational Intelligence and Communication Networks, CICN 2020
Sources of information:
Directorio de Producción Científica
Scopus