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Title: Profile-driven memory bandwidth management for accelerators and CPUs in QoS-enabled platforms
The proliferation of multi-core, accelerator-enabled embedded systems has introduced new opportunities to consolidate real-time systems of increasing complexity. But the road to build confidence on the temporal behavior of co-running applications has presented formidable challenges. Most prominently, the main memory subsystem represents a performance bottleneck for both CPUs and accelerators. And industry-viable frameworks for full-system main memory management and performance analysis are past due. In this paper, we propose our Envelope-aWare Predictive model, or E-WarP for short. E-WarP is a methodology and technological framework to (1) analyze the memory demand of applications following a profile-driven approach; (2) make realistic predictions on the temporal behavior of workload deployed on CPUs and accelerators; and (3) perform saturation-aware system consolidation. This work aims at providing the technological foundations as well as the theoretical grassroots for truly workload-aware analysis of real-time systems. This work combines traditional CPU-centric bandwidth regulation techniques with state-of-the-art hardware support for memory traffic shaping via the ARM QoS extensions. We make three key observations. First, our profile-driven methodology achieves, on average, 6% over-prediction on the runtime of bandwidth-regulated applications. Second, we experimentally validate that the calculated bounds hold system-wide if the main memory subsystem operates below saturation. Third, we show that the E-WarP methodology is practical even when applications exhibit input-dependent memory access patterns. We provide a full implementation of our techniques on a commercial platform (NXP S32V234).  more » « less
Award ID(s):
2008799
NSF-PAR ID:
10332474
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Real-Time Systems
ISSN:
0922-6443
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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