research-article

Memory-Centric Communication Mechanism for Real-time Autonomous Navigation Applications

Authors:

jiangming jinAuthors Info & Claims

ICPP '20: Proceedings of the 49th International Conference on Parallel Processing

Article No.: 33, Pages 1 - 11

https://doi.org/10.1145/3404397.3404459

Published: 17 August 2020 Publication History

Abstract

There has been a remarkable increase in the speed of AI development over the past few years. Artificial intelligence and deep learning techniques are blooming and expanding in all forms to every sector possible. With the emerging intelligent autonomous navigation systems, both memory allocation and data movement are becoming the main bottlenecks in inter-process communication procedures, especially in supporting various types of messages between multiple programming languages. To reduce significant memory allocation and data movement cost, we propose a novel memory-centric mechanism, which includes a virtual layer based architecture and a pre-record memory allocation algorithm. Furthermore, we implement a memory-centric communication framework named Z-framework based on the proposed mechanism to achieve high efficient IPC procedures in autonomous navigation systems. Experimental results show that Z-framework is able to gain up to 41% and 35% performance improvement compared with the approach used in ROS2, which is an industry standard and the state-of-the-art approach used in CyberRT, respectively.

References

[1]

[1] Abadi, M., et al. Tensorflow: A system for large-scale machine learning. In Symposium on Operating Systems Design and Implementation, 2016.

Digital Library

[2]

[2] Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., ... Darrell, T. (2014, November). Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the 22nd ACM international conference on Multimedia (pp. 675-678). ACM.

Digital Library

[3]

[3] Chen, T., Li, M., Li, Y., Lin, M., Wang, N., Wang, M., ... Zhang, Z. (2015). Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems. arXiv preprint arXiv:1512.01274.

[4]

[4] Bauckhage C. Numpy/scipy recipes for data science: k-medoids clustering. Researchgate. Net, February, 2015.

[5]

[5] Ziyue Jiang, Yifan Gong, JidongZhai, Yuping Wang, Wei Liu, Hao Wu, Jiangming Jin. Message Passing Optimization in Robot Operating System. Network and Parallel Computing, 2019

[6]

[6] M. Quigley, K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, A. Y. Ng. ROS: an open-source Robot Operating System. Proc. of IEEE International Conference on Robotics and Automation Workshop on Open Source Software, vol. 3. 2009.

[7]

[7] S. Cousins, B. Gerkey, K. Conley, W. Garage. Sharing software with ROS. IEEE Robotics & Automation Magazine, vol. 17, no. 2, pp. 12-14, 2010.

[8]

[8] Maruyama Y, Kato S, Azumi T. Exploring the performance of ROS2. InProceedings of the 13th International Conference on Embedded Software 2016 Oct 1 (p. 5). ACM.

[9]

[9] G. Pardo-Castellote. OMG Data-Distribution Service: Architectural Overview. Proc. of IEEE International Conference on Distributed Computing Systems Workshops. 2003.

[10]

[10] ROS2. http://design.ros2.org/articles/ros_on_dds.html.

[11]

[11] Waypoint. https://en.wikipedia.org/wiki/Waypoint.

[12]

[12] Rao, Qing, and J. Frtunikj. Deep Learning for Self-Driving Cars: Chances and Challenges. 2018 IEEE/ACM 1st International Workshop on Software Engineering for AI in Autonomous Systems (SEFAIAS) 2018.

Digital Library

[13]

[13] Baidu Apollo. http://apollo.auto/cyber.html

[14]

[14] ethzasl_message_transport. Website Available: https://github.com/ethz-asl/ros-message-transport.

[15]

[15] N. Dantam, M. Stilman, ”Robust and Efficient Communication for Real-Time Multi-Process Robot Software”, in IEEE-RAS International Conference on Humanoid Robots (Humanoids), Osaka, Japan, 2012.

[16]

[16] P. Druschel, L. L. Peterson, ”Fbufs: A High-Bandwidth Cross-Domain Transfer Facility”, in Proceedings of the 14th ACM Symposium on Operating Systems Principles (SOSP), Asheville, NC, USA, 1993.

Digital Library

[17]

[17] Mi, Zeyu, et al. ”Skybridge: Fast and secure inter-process communication for microkernels.” Proceedings of the Fourteenth EuroSys Conference 2019. 2019.

Digital Library

[18]

[18] A. Elkady and T. M. Sobh. Robotics Middleware: A Comprehensive Literature Survey and Attribute-Based Bibliography. Journal of Robotics. 2012.

[19]

[19] Protocol Buffers. User Guide. https://developers.google.com/protocol-buffers/docs/overview?csw=1

[20]

[20] Einhorn, Erik, et al. ”Mira-middleware for robotic applications.” 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2012.

[21]

[21] Huang, Albert S., Edwin Olson, and David C. Moore. LCM: Lightweight communications and marshalling. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE. 2010.

[22]

[22] Rao A, Visali M, Shailendra S, et al. Reliable robotic communication using multi-path TCP[C]//2017 9th International Conference on Communication Systems and Networks (COMSNETS). IEEE, 2017: 429-430.

[23]

[23] Metta, Giorgio, Paul Fitzpatrick, and Lorenzo Natale. YARP: yet another robot platform. International Journal of Advanced Robotic Systems 3.1 (2006).

[24]

[24] Data Distribution Services (DDS) v1.4, 2015. http://www.omg.org/spec/DDS/1.4/.

[25]

[25] Yu-Ping Wang, Wende Tan, Xu-Qiang Hu, Dinesh Manocha and Shi-Min Hu. TZC: Efficient Inter-Process Communication for Robotics Middleware with Partial Serialization, 2018; arXiv:1810.00556.

[26]

[26] Wei H, Shao Z, Huang Z, Chen R, Guan Y, Tan J, Shao Z. RT-ROS: A real-time ROS architecture on multi-core processors. Future Generation Computer Systems. 2016 Mar 1;56:171-8.

[27]

[27] Y. Wang, S. Liu, X. Wu, and W. Shi, ”CAVBench: A benchmark suite for connected and autonomous vehicles,” in 2018 IEEE/ACM Symposium on Edge Computing (SEC), 2018, pp. 30–42.

[28]

[28] Sugata Y, Ohkawa T, Ootsu K, Yokota T. Acceleration of publish/subscribe messaging in ROS-compliant FPGA component. InProceedings of the 8th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies 2017 Jun 7 (p. 13). ACM.

[29]

[29] Wei H, Huang Z, Yu Q, Liu M, Guan Y, Tan J. RGMP-ROS: A real-time ROS architecture of hybrid RTOS and GPOS on multi-core processor. In2014 IEEE International Conference on Robotics and Automation (ICRA) 2014 May 31 (pp. 2482-2487). IEEE.

[30]

[30] Saito Y, Sato F, Azumi T, Kato S, Nishio N. ROSCH: Real-Time Scheduling Framework for ROS. In2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA) 2018 Aug 28 (pp. 52-58). IEEE.

[31]

[31] Liétar, Paul, et al. ”Snmalloc: a message passing allocator.” Proceedings of the 2019 ACM SIGPLAN International Symposium on Memory Management. 2019.

Digital Library

[32]

[32] Bonwick, Jeff. ”The slab allocator: An object-caching kernel memory allocator.” USENIX summer. Vol. 16. 1994.

[33]

[33] Huang, Xiaohuang, et al. ”Xmalloc: A scalable lock-free dynamic memory allocator for many-core machines.” 2010 10th IEEE International Conference on Computer and Information Technology. IEEE, 2010.

Digital Library

[34]

[34] Ghemawat, Sanjay, and Paul Menage. ”Tcmalloc: Thread-caching malloc.” (2009).

[35]

[35] Masmano, Miguel, et al. ”A constant-time dynamic storage allocator for real-time systems.” Real-Time Systems 40.2 (2008): 149-179.

Digital Library

[36]

[36] Evans, Jason. ”A scalable concurrent malloc (3) implementation for FreeBSD.” Proc. of the bsdcan conference, ottawa, canada. 2006.

Cited By

Wu HJin JZhai JGong YLiu W(2021)Accelerating GPU Message Communication for Autonomous Navigation Systems2021 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/Cluster48925.2021.00029(181-191)Online publication date: Sep-2021
https://doi.org/10.1109/Cluster48925.2021.00029

Recommendations

A Design to Adapt Microkernel Inter-process Communication Mechanism
ICIIP '18: Proceedings of the 3rd International Conference on Intelligent Information Processing

In order to improve the efficiency of inter-process communication among microkernel operating systems, this paper proposes an inter-process communication mechanism for microkernels. The mechanism runs IPC (Inter-Process Communication) as a set of ...
Architecture of autonomous vehicle simulation and control framework
AIR '15: Proceedings of the 2015 Conference on Advances In Robotics

With the current advances in Autonomous Navigation Systems for Self Driving Vehicles, there is a need for specialized and focused software architecture for ease in simulating the vehicle behavior and associated modules such as perception, drive by wire ...
Real-time hierarchical POMDPs for autonomous robot navigation

This paper proposes a new hierarchical formulation of POMDPs for autonomous robot navigation that can be solved in real-time, and is memory efficient. It will be referred to in this paper as the Robot Navigation-Hierarchical POMDP (RN-HPOMDP). The RN-...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

ICPP '20: Proceedings of the 49th International Conference on Parallel Processing

August 2020

844 pages

ISBN:9781450388160

DOI:10.1145/3404397

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 August 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

ICPP '20

ICPP '20: 49th International Conference on Parallel Processing

August 17 - 20, 2020

AB, Edmonton, Canada

Acceptance Rates

Overall Acceptance Rate 91 of 313 submissions, 29%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
190
Total Downloads

Downloads (Last 12 months)28
Downloads (Last 6 weeks)3

Reflects downloads up to 15 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Wu HJin JZhai JGong YLiu W(2021)Accelerating GPU Message Communication for Autonomous Navigation Systems2021 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/Cluster48925.2021.00029(181-191)Online publication date: Sep-2021
https://doi.org/10.1109/Cluster48925.2021.00029

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten