Abstract
Deep learning accelerators are pivotal in accelerating computation-intensive tasks in modern AI applications. Optimizing the utilization of system resources, including shared cache, on-chip SRAM, and data movement mechanisms, is crucial for achieving superior performance and energy efficiency. In this study, we propose an efficient system architecture specifically tailored for deep learning workloads. Our architecture enables to reconfigure the last level cache as a scratchpad with prefetch capability, which eliminates cache misses and thereby offers resource efficiency, improved performance, and energy efficiency. By implementing a strategy to overlap accelerator execution with data movement, we achieved remarkable results, including a 14× speedup and %5 reduction in energy consumption for the ResNet50 benchmark when compared to the base system configuration. These findings demonstrate the substantial benefits of incorporating prefetch support and scratchpad reconfiguration in the last level cache, leading to enhanced performance and energy efficiency in real-world deep learning accelerator applications.
Original language | English |
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Title of host publication | ICECS 2023 - 2023 30th IEEE International Conference on Electronics, Circuits and Systems |
Subtitle of host publication | Technosapiens for Saving Humanity |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350326499 |
DOIs | |
Publication status | Published - 2023 |
Event | 30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023 - Istanbul, Turkey Duration: 4 Dec 2023 → 7 Dec 2023 |
Publication series
Name | ICECS 2023 - 2023 30th IEEE International Conference on Electronics, Circuits and Systems: Technosapiens for Saving Humanity |
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Conference
Conference | 30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023 |
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Country/Territory | Turkey |
City | Istanbul |
Period | 4/12/23 → 7/12/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- accelerator utilization
- cache configuration
- cache design
- cache hierarchy
- data availability
- deep learning accelerators
- energy efficiency
- latency
- prefetching mechanism