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Efficient sharing of linked DMA channels on multi-sensor devices by LDMA task scheduler
Conference paper

Efficient sharing of linked DMA channels on multi-sensor devices by LDMA task scheduler

You-Ren Shen, Bo-Yan Huang, Chang-Lin Shih, Davy P. Y. Wong and Pai H. Chou
SYSTOR 2022 - Proceedings of the 15th ACM International Conference on Systems and Storage Conference, pp.40-50
06/2022

Abstract

linked direct memory access (LDMA) lower power multi-sensor real-time systems scheduling wearable medical device Computer Science Applications Hardware and Architecture Software Electrical and Electronic Engineering
Modern microcontroller units (MCUs) support enhanced direct memory access (DMA) such as Linked DMA (LDMA) mechanisms that not only offload bulk I/O from the processor core but also support simple commands to minimize processor intervention between bulk transfers. However, straightforward offloading to dedicated channels results in full occupancy of the channel resources even if the actual I/O load is low. To address this problem, we propose an LDMA task scheduler that schedules groups of tasks to enable their shared access to the same set of channels. When applied to a real-life multi-sensor device, the proposed scheme reduces total channel occupancy from 100% down to 32.95% while incurring minimal processor overhead of 0.1%, thereby enabling offloading of twice as many I/O tasks as the fixed channel allocation scheme.

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