TY - GEN
T1 - Debugging FPGA-accelerated Real-time Systems
AU - Geier, Martin
AU - Brandle, Marian
AU - Faller, Dominik
AU - Chakraborty, Samarjit
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/4
Y1 - 2020/4
N2 - The high computation/communication requirements along with reliability needs and limited power budgets necessitate complex processing platforms for emerging autonomous systems. Due to the current focus on performance, however, such platforms are increasingly difficult to predict and analyze. This holds true in terms of both performance (e.g., behavioral and temporal) aspects and power consumption. Ensuring functional safety thus requires new techniques to analyze performance, predictability and power. In this paper, we thus propose a novel hybrid tracing methodology to monitor (and, subsequently, optimize) temporal, functional and energy-related properties of Real-time Systems (RTSs). We target current Programmable SoCs (pSoCs) integrating a fixed-function System-on-Chip (SoC) with flexible Field Programmable Gate Array (FPGA) fabric. Although such heterogeneous systems are well suited for high-end, mixed-hardware/software real-time pipelines, they also offer more complex performance/energy trade-offs than software-only platforms. To systematically exploit this complexity, we present a resource-efficient trace IP core for the pSoC's fabric and an external measurement/interface system - jointly capturing hybrid power/state traces for subsequent (i.e., offline) analysis. By fusing state data from our IP core with events-of-interest gathered from power traces of pSoC and co-monitored I/O components, we gain a holistic view on temporal RTS aspects. Events and synchronized multi-rail power data jointly extend the debugging coverage via automated identification of processing phases, computation of energy baselines, and estimation of potential savings. Our solution thus integrates functional, temporal and energy monitoring into a single, unified workflow, which, in contrast to traditional separate tools, delivers valuable new insights helpful during debugging and reduces both cost and effort. Experimental evaluations on a Zynq-based Visual Servoing System show the method's various benefits.
AB - The high computation/communication requirements along with reliability needs and limited power budgets necessitate complex processing platforms for emerging autonomous systems. Due to the current focus on performance, however, such platforms are increasingly difficult to predict and analyze. This holds true in terms of both performance (e.g., behavioral and temporal) aspects and power consumption. Ensuring functional safety thus requires new techniques to analyze performance, predictability and power. In this paper, we thus propose a novel hybrid tracing methodology to monitor (and, subsequently, optimize) temporal, functional and energy-related properties of Real-time Systems (RTSs). We target current Programmable SoCs (pSoCs) integrating a fixed-function System-on-Chip (SoC) with flexible Field Programmable Gate Array (FPGA) fabric. Although such heterogeneous systems are well suited for high-end, mixed-hardware/software real-time pipelines, they also offer more complex performance/energy trade-offs than software-only platforms. To systematically exploit this complexity, we present a resource-efficient trace IP core for the pSoC's fabric and an external measurement/interface system - jointly capturing hybrid power/state traces for subsequent (i.e., offline) analysis. By fusing state data from our IP core with events-of-interest gathered from power traces of pSoC and co-monitored I/O components, we gain a holistic view on temporal RTS aspects. Events and synchronized multi-rail power data jointly extend the debugging coverage via automated identification of processing phases, computation of energy baselines, and estimation of potential savings. Our solution thus integrates functional, temporal and energy monitoring into a single, unified workflow, which, in contrast to traditional separate tools, delivers valuable new insights helpful during debugging and reduces both cost and effort. Experimental evaluations on a Zynq-based Visual Servoing System show the method's various benefits.
UR - http://www.scopus.com/inward/record.url?scp=85086761751&partnerID=8YFLogxK
U2 - 10.1109/RTAS48715.2020.00010
DO - 10.1109/RTAS48715.2020.00010
M3 - Conference contribution
AN - SCOPUS:85086761751
T3 - Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
SP - 350
EP - 363
BT - Proceedings - 2020 IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2020
Y2 - 21 April 2020 through 24 April 2020
ER -