Grant: Discovery Grants Program - Individual
Toronto Metropolitan University
$24,000.00
Utilizing Run-Time Reconfiguration to Reduce the Static Power Consumption of FPGAs for Mobile Applications
FY 2022-23
Summary
The goal of this research is to reduce the power consumption of FPGAs to the level of the lowest power consuming processors through the use of run-time reconfiguration. Run-time reconfiguration, the ability of an FPGA to change its functionality while under operation, has been successfully used in many commercial FPGAs to expand the logic capacity of FPGAs to beyond what can be manufactured by current silicon process technologies. For portable devices with limited battery power, however, the logic capacity of an FPGA is not limited by current process technologies but by the low power output of small batteries. Run-time reconfiguration potentially can allow FPGAs to gracefully trade performance for reduced power consumption in order to bring the power consumption of current low power FPGAs to the level of the lowest power consuming processors. FPGAs are an important platform for implementing a variety of digital applications due to their short time to market, re-programmability and low non-recurring engineering costs. While FPGAs have been successfully used in many applications including digital signal processing, aerospace, medical imaging, computer vision, speech recognition, and ASIC prototyping, they have not been widely used in mobile applications due to their high static power consumption. In particular, the static power consumption of today's low power FPGAs is significantly higher than the static power consumption of the lowest power consuming processors. Consequently, constrained by the limited power output of small batteries, current mobile devices are mainly limited to the use of low-power processors despite the fact that these processors have extremely low performance and energy efficiency especially when compared to FPGAs. In this work, we will characterize the effect of run-time reconfiguration on the area, performance, and power efficiency of FPGAs. In particular, we will develop new FPGA area and performance models to accurately measure the effect of run-time reconfiguration on the performance, dynamic and static power consumption of FPGAs. We will then develop new FPGA architectures and tools to effectively utilize run-time reconfiguration under the power constraint of mobile applications and empirically evaluate the effect of run-time reconfiguration on the area, performance and power efficiency of low power FPGAs.
Program
Discovery Grants Program - Individual
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2017-04405
Name nom
Ye, Andy
Department département
Electrical, Computer and Biomedical Engineering - Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2017
Award amount
24000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Installment
inst:6
Partie
1
Nb partie
6
Application title
Utilizing Run-Time Reconfiguration to Reduce the Static Power Consumption of FPGAs for Mobile Applications
Application summary
The goal of this research is to reduce the power consumption of FPGAs to the level of the lowest power consuming processors through the use of run-time reconfiguration. Run-time reconfiguration, the ability of an FPGA to change its functionality while under operation, has been successfully used in many commercial FPGAs to expand the logic capacity of FPGAs to beyond what can be manufactured by current silicon process technologies. For portable devices with limited battery power, however, the logic capacity of an FPGA is not limited by current process technologies but by the low power output of small batteries. Run-time reconfiguration potentially can allow FPGAs to gracefully trade performance for reduced power consumption in order to bring the power consumption of current low power FPGAs to the level of the lowest power consuming processors. FPGAs are an important platform for implementing a variety of digital applications due to their short time to market, re-programmability and low non-recurring engineering costs. While FPGAs have been successfully used in many applications including digital signal processing, aerospace, medical imaging, computer vision, speech recognition, and ASIC prototyping, they have not been widely used in mobile applications due to their high static power consumption. In particular, the static power consumption of today's low power FPGAs is significantly higher than the static power consumption of the lowest power consuming processors. Consequently, constrained by the limited power output of small batteries, current mobile devices are mainly limited to the use of low-power processors despite the fact that these processors have extremely low performance and energy efficiency especially when compared to FPGAs. In this work, we will characterize the effect of run-time reconfiguration on the area, performance, and power efficiency of FPGAs. In particular, we will develop new FPGA area and performance models to accurately measure the effect of run-time reconfiguration on the performance, dynamic and static power consumption of FPGAs. We will then develop new FPGA architectures and tools to effectively utilize run-time reconfiguration under the power constraint of mobile applications and empirically evaluate the effect of run-time reconfiguration on the area, performance and power efficiency of low power FPGAs.