ASF: An Adaptive Scaling Framework for High Scalability of XOR-Based RAID Systems

Sponsored by NSF CNS-CSR

Abstract:

Explosive growth in data volume, heterogeneity, and complexity imposes unprecedented challenges in data analysis and organization in data centers. RAID particularly XOR-based RAID plays an important role to provide both reliability and high performance storage services for these data centers. However, they suffer from problems on the scalability issue due to multi-folded factors, including: heterogeneous RAID layouts and various erasure codes, high overhead of existing scaling process to significantly downgrade the storage performance, and lack of bidirectional scaling support.

The objective of this project is to address the scalability challenge for storage systems in large data centers. This project designs novel techniques to exploit XOR-based parity codes to achieve efficient scaling, develops a series of scalable XOR-based erasure codes to bridge the relations among heterogeneous RAID forms for interoperability, and integrates various erasure codes in a framework to provide a unified user interface for RAID scaling.

Personnel

- Principal Investigator

- Collaborators

- Post Doctoral Researcher

- Graduate Students

Recent Publications

  1. *Y. Guo, Q. Liu, W. Xiao, *P. Huang, N. Podhorszki, S. Klasky, and X. He, “SELF: A High Performance and Bandwidth Efficient Approach to Exploiting Die-stacked DRAM as Part of Memory”, Proceedings of the IEEE 25th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2017), Banff, Canada, September 20-22, 2017 (acceptance rate: 26/84=31%).
  2. Y. Zhou, F. Wu, P. Huang, X. He, C. Xie, and J. Zhou, “Understanding and Alleviating the Impact of the Flash Address Translation on Solid State Devices”, ACM Transactions on Storage, Vol. 13, No. 2, June 2017.
  3. *T. Yao, J. Wan, *P. Huang, X. He, Q. Gui, F. Wu, and C. Xie, “A Light-weight Compaction Tree to Reduce I/O Amplification toward Efficient Key-Value Stores”, the 33rd International Conference on Massive Storage Systems and Technology (MSST), Santa Clara, CA, May 15-19, 2017 (acceptance rate: 19/60=31.6%).
  4. *W. Liu, *P. Huang, *K. Tang, *T. Lu, K. Zhou, C. Li, and X. He, “LAMS: A Latency-Aware Memory Scheduling Policy for Modern DRAM Systems”, Proceedings of the 35th IEEE International Performance Computing and Communications Conference (IPCCC), December 9-11, 2016 (acceptance rate: 48/194=24.7%).
  5. J. Fang, S. Wan, *P. Huang, X. He, and C. Xie, “Achieving High Reliability via Expediting the Repair of Critical Blocks in Replicated Storage Systems”, Proceedings of the 35th IEEE Symposium on Reliable Distributed Systems (SRDS), Budapest, Hungary, September 26-29, 2016 (acceptance rate: 29/83=35%).
  6. W. Liu, *P. Huang, *T. Lu, X. He, H. Wang, and K. Zhou, “Improve Restore Speed in Deduplication Systems Using Segregated Cache”, IEEE MASCOTS’2016, London, UK, September 19-21, 2016.
  7. *P. Huang, W. Liu, *K. Tang, X. He and K. Zhou, “ROP: Alleviating Refresh Overheads via Reviving the Memory System in Frozen Cycles”, Proceedings of the International Conference on Parallel Processing (ICPP), Philadelphia, PA, August 16-19, 2016 (acceptance rate: 53/251=21%).
  8. *P. Subedi, *P. Huang, *T. Liu, J. Moore, S. Skelton, and X. He, “CoARC: Co-operative, Aggressive Recovery and Caching for Failures in Erasure Coded Hadoop”, Proceedings of the International Conference on Parallel Processing (ICPP), Philadelphia, PA, August 16-19, 2016 (acceptance rate: 72/251=28.7%).
  9. P. Zhang, *P. Huang, X. He, H. Wang, L. Yan, and K. Zhou, “RMD: A Resemblance and Mergence based Approach for High Performance Deduplication”, Proceedings of the International Conference on Parallel Processing (ICPP), Philadelphia, PA, August 16-19, 2016 (acceptance rate: 72/251=28.7%).
  10. W. Liu, P. Huang, K. Tang, K. Zhou, and X. He, “CAR: A Compression-Aware Refresh Approach to Improve Memory Performance and Energy Efficiency”, Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science (SIGMETRICS), France, June 2016.
  11. M. Zhang, F. Wu, X. He, *P. Huang, S. Wang and C. Xie, “REAL: A Retention Error Aware LDPC Decoding Scheme to Improve NAND Flash Read Performance”, Proceedings of the 32nd International Conference on Massive Storage Systems and Technology (MSST), Santa Clara, CA, May 2-6, 2016.
  12. *T. Lu, *M. Stuart, *P. Huang, *Y. Guo, X. He, and M. Zhang, “Successor: Proactive Cache Warm-up of Destination Hosts in Virtual Machine Migration Contexts”, Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), San Francisco, CA, April 10-15, 2016 (acceptance rate: 300/1644=18.2%).
  13. *Y. Guo, *P. Huang, *B. Young, *T. Lu, X. He, and Q. Liu, “Alleviating DRAM Refresh Overhead via Inter-rank Piggyback Caching”, The 23rd IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), October 5-7, 2015 (acceptance rate: 21/87=24.1%).
  14. C. Du, *C. Wu, J. Li, M. Guo, and X. He, “BPS: A Balanced Partial Stripe Write Scheme to Improve the Performance of RAID-6”, Proc. Of the IEEE Cluster, Chicago, Illinois, USA, Sept. 8-11, 2015 (acceptance rate: 38/157=24%).
  15. Y. Guo, P. Huang, B. Young, T. Lu, X. He, and Q. Liu, “Alleviating DRAM Refresh Overhead via Inter-rank Piggyback Caching”, The 23rd IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), October 5-7, 2015.
  16. C. Du, C. Wu, J. Li, M. Guo, and X. He, “BPS: A Balanced Partial Stripe Write Scheme to Improve the Performance of RAID-6”, Proc. Of the IEEE Cluster, Chicago, Illinois, USA, Sept. 8-11, 2015 (acceptance rate: 38/157=24%).
  17. C. Wu, X. He, J. Li, and M. Guo, “Code 5-6: An Efficient MDS Array Coding Scheme to Accelerate Online RAID Level Migration”, Proc of the International Conference on Parallel Processing (ICPP), 2015, Beijing, China (acceptance rate: 99/325=32.5%).
  18. S. Li, Q. Cao, S. Wan, W. Zhang, C. Xie, X. He, S. Pradeep, “PPM: A Partitioned and Parallel Matrix Algorithm to Accelerate Encoding/Decoding Process of Asymmetric Parity Erasure Codes”, Proc of the International Conference on Parallel Processing (ICPP), 2015, Beijing, China (acceptance rate: 99/325=32.5%).
  19. P. Subedi, P. Huang, B. Young, and X. He, “FINGER: A Novel Erasure Coding Scheme Using Fine Granularity Blocks to Improve Hadoop Write and Update Performance,” Proc. Of the 10th IEEE International Conference on Networking, Architecture, and Storage (NAS), August 6-7, 2015, Boston, MA (acceptance rate: 30/94=32%).
  20. Y. Yu, W. Xiao, X. He, H. Guo, and Y. Wang, “A Stall-Aware Warp Scheduling for Dynamically Optimizing Thread-level Parallelism in GPGPUs”, the 29th International Conference on Supercomputing (ICS), June 8-11, Newport Beach, CA (acceptance rate: 40/160=25%).
  21. Y. Zhou, F. Wu, P. Huang, X. He, C. Xie, and J. Zhou, “An Efficient Page-level FTL to Optimize Address Translation in Flash Memory”, The European Conference on Computer Systems (EuroSys), April 2015 (acceptance rate: 32/150=21%).
  22. P. Subedi, P. Huang, X. He, M. Zhang, and J. Han, "A Hybrid Erasure-Coded ECC Scheme to Improve Performance and Reliability of Solid State Drives", 33rd IEEE International Performance Computing and Communications Conference, Austin, TX, December 2014.
  23. S. Li and X. He and S. Wan and Y. Guo and P. Huang and D. Chen and Q. Cao and C. Xie (2014). Exploiting Decoding Computational Locality to Improve the I/O Performance of an XOR-coded Storage Cluster under Concurrent Failures. International Symposium on Reliable Distributed Systems (SRDS). Nara, Japan.

Sponsors