CaMDN: Enhancing Cache Efficiency for Multi-tenant DNNs on Integrated NPUs

With the rapid development of DNN applications, multi-tenant execution, where multiple DNNs are co-located on a single SoC, is becoming a prevailing trend. Although many methods are proposed in prior works to improve multi-tenant performance, the impact of shared cache is not well studied. This paper proposes CaMDN, an architecture-scheduling co-design to enhance cache efficiency for multi-tenant DNNs on integrated NPUs. Specifically, a lightweight architecture is proposed to support model-exclusive, NPU-controlled regions inside shared cache to eliminate unexpected cache contention. Moreover, a cache scheduling method is proposed to improve shared cache utilization. In particular, it includes a cache-aware mapping method for adaptability to the varying available cache capacity and a dynamic allocation algorithm to adjust the usage among co-located DNNs at runtime. Compared to prior works, CaMDN reduces the memory access by 33.4% on average and achieves a model speedup of up to 2.56 × (1.88 × on average).

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11132424
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

CaMDN: Enhancing Cache Efficiency for Multi-tenant DNNs on Integrated NPUs

Xiaojian Liao, Limin Xiao, Lin Sun, Tianhao Cai et al.
IoT and Edge/Fog Computing
article

CaMDN: Enhancing Cache Efficiency for Multi-tenant DNNs on Integrated NPUs

Xiaojian Liao, Limin Xiao, Lin Sun, Tianhao Cai, Liang Wang, Meng Han, Zeyu Wang
article en

Abstract

With the rapid development of DNN applications, multi-tenant execution, where multiple DNNs are co-located on a single SoC, is becoming a prevailing trend. Although many methods are proposed in prior works to improve multi-tenant performance, the impact of shared cache is not well studied. This paper proposes CaMDN, an architecture-scheduling co-design to enhance cache efficiency for multi-tenant DNNs on integrated NPUs. Specifically, a lightweight architecture is proposed to support model-exclusive, NPU-controlled regions inside shared cache to eliminate unexpected cache contention. Moreover, a cache scheduling method is proposed to improve shared cache utilization. In particular, it includes a cache-aware mapping method for adaptability to the varying available cache capacity and a dynamic allocation algorithm to adjust the usage among co-located DNNs at runtime. Compared to prior works, CaMDN reduces the memory access by 33.4% on average and achieves a model speedup of up to 2.56 × (1.88 × on average).

San’an Optoelectronics (China) (CN), Beihang University (CN), Tsinghua University (CN)
Openalex Percentile: Top 72%
IoT and Edge/Fog Computing
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