The current over-provisioned heterogeneous multicores require effective run-time optimization strategies, and the run-time power monitoring subsystem is paramount for their success. Several state-of-the-art methodologies address the design of a run-time power monitoring infrastructure for generic computing platforms. However, the power model's training requires time-consuming gate-level simulations that, coupled with the everincreasing complexity of the modern heterogeneous platforms, dramatically hinder the usability of such solutions. This paper introduces Blink, a scalable framework for the fast and automated design of run-time power monitoring infrastructures targeting computing platforms implemented on FPGA. Blink optimizes the time-to-solution to deliver the run-time power monitoring infrastructure by replacing traditional methodologies' gate-level simulations and power trace computations with behavioral simulations and direct power trace measurements. Applying Blink to multiple designs mixing a set of HLS-generated accelerators from a state-of-the-art benchmark suite demonstrates an average time-to-solution speedup of 18 times without affecting the quality of the run-time power estimates.

Blink: Fast Automated Design of Run-Time Power Monitors on FPGA-Based Computing Platforms

Galimberti, Andrea;Piccoli, Michele;Zoni, Davide
2024-01-01

Abstract

The current over-provisioned heterogeneous multicores require effective run-time optimization strategies, and the run-time power monitoring subsystem is paramount for their success. Several state-of-the-art methodologies address the design of a run-time power monitoring infrastructure for generic computing platforms. However, the power model's training requires time-consuming gate-level simulations that, coupled with the everincreasing complexity of the modern heterogeneous platforms, dramatically hinder the usability of such solutions. This paper introduces Blink, a scalable framework for the fast and automated design of run-time power monitoring infrastructures targeting computing platforms implemented on FPGA. Blink optimizes the time-to-solution to deliver the run-time power monitoring infrastructure by replacing traditional methodologies' gate-level simulations and power trace computations with behavioral simulations and direct power trace measurements. Applying Blink to multiple designs mixing a set of HLS-generated accelerators from a state-of-the-art benchmark suite demonstrates an average time-to-solution speedup of 18 times without affecting the quality of the run-time power estimates.
2024
2024 31st IEEE International Conference on Electronics, Circuits and Systems (ICECS)
run-time power monitoring , electronic design automation , FPGA
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1281575
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