Name
Title | ||
|---|---|---|
Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform |
Abstract | ||
|---|---|---|
Cutting-edge embedded system applications, such as self-driving cars and unmanned drone software, are reliant on integrated CPU/GPU platforms for their DNNs-driven workload, such as perception and other highly parallel components. In this work, we set out to explore the hidden performance implication of GPU memory management methods of integrated CPU/GPU architecture. Through a series of experiments on micro-benchmarks and real-world workloads, we find that the performance under different memory management methods may vary according to application characteristics. Based on this observation, we develop a performance model that can predict system overhead for each memory management method based on application characteristics. Guided by the performance model, we further propose a runtime scheduler. By conducting per-task memory management policy switching and kernel overlapping, the scheduler can significantly relieve the system memory pressure and reduce the multitasking co-run response time. We have implemented and extensively evaluated our system prototype on the NVIDIA Jetson TX2, Drive PX2, and Xavier AGX platforms, using both Rodinia benchmark suite and two real-world case studies of drone software and autonomous driving software. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/RTAS48715.2020.00007 | 2020 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS) |
Keywords | DocType | ISSN |
per-task memory management policy switching,system memory pressure,Drive PX2,Xavier AGX platforms,autonomous driving software,autonomous driving platform,embedded system applications,self-driving cars,unmanned drone software,system overhead,DNN-driven workload,Integrated CPU-GPU memory management,multitasking corun response time,NVIDIA Jetson TX2,Rodinia benchmark suite,deep neural networks | Conference | 1545-3421 |
ISBN | Citations | PageRank |
978-1-7281-5500-5 | 2 | 0.36 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bateni Soroush | 1 | 2 | 0.36 |
| Wang Zhendong | 2 | 2 | 0.36 |
| Yuankun Zhu | 3 | 7 | 2.11 |
| Yang Hu | 4 | 217 | 23.66 |
| Cong Liu | 5 | 780 | 56.17 |