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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 洪士灝(Shih-Hao Hung) | |
| dc.contributor.author | Hang-Hsun Fan | en |
| dc.contributor.author | 范航熏 | zh_TW |
| dc.date.accessioned | 2022-11-24T09:27:05Z | - |
| dc.date.available | 2022-11-24T09:27:05Z | - |
| dc.date.copyright | 2021-11-08 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-04 | |
| dc.identifier.citation | [1] Crypto++ library 8.5. https://www.cryptopp.com/. Accessed: 2021093. [2] Google's fast compressor/decompressor. https://github.com/google/snappy. Accessed: 2021093. [3] Infiniband overview. https://linuxcluster.files.wordpress.com/2012/10/tcp_bypass_overview.pdf. Accessed: 2021099. [4] Introduction to InfiniBand. https://www.mellanox.com/pdf/whitepapers/IB_Intro_WP_190.pdf. Accessed: 20210923. [5] Introduction to RDMA. https://zcopy.wordpress.com/2010/10/08/quick-concepts-part-1-%E2%80%93-introduction-to-rdma/. Accessed: 20210923. [6] Understanding iWARP: Eliminating Overhead and Latency in multiGb Ethernet Networks. http://web.cse.ohio-state.edu/~panda.2/788/papers/1k_understanding_iwarp.pdf. Accessed: 20210923. [7] M. K. Aguilera, N. Amit, I. Calciu, X. Deguillard, J. Gandhi, S. Novakovic, A. Ramanathan, P. Subrahmanyam, L. Suresh, K. Tati, R. Venkatasubramanian, and M. Wei. Remote regions: A simple abstraction for remote memory. In Proceedings of the 2018 USENIX Conference on Usenix Annual Technical Conference, USENIX ATC'18, page 775–787, USA, 2018. USENIX Association. [8] E. Amaro, C. BrannerAugmon, Z. Luo, A. Ousterhout, M. K. Aguilera, A. Panda, S. Ratnasamy, and S. Shenker. Can far memory improve job throughput? In Proceedings of the Fifteenth European Conference on Computer Systems, EuroSys' 20, New York, NY, USA, 2020. Association for Computing Machinery. [9] I. Calciu, M. T. Imran, I. Puddu, S. Kashyap, H. A. Maruf, O. Mutlu, and A. Kolli. Rethinkingsoftwareruntimesfordisaggregatedmemory. InProceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2021, page 79–92, New York, NY, USA, 2021. Association for Computing Machinery. [10] A. Dragojević, D. Narayanan, O. Hodson, and M. Castro. Farm: Fast remote memory. In Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation, NSDI’14, page 401–414, USA, 2014. USENIX Association. [11] A. Dragojević, D. Narayanan, E. B. Nightingale, M. Renzelmann, A. Shamis, A. Badam, and M. Castro. No Compromises: Distributed Transactions with Consistency, Availability, and Performance, page 54–70. Association for Computing Machinery, New York, NY, USA, 2015. [12] P.X.Gao,A.Narayan,S.Karandikar,J.Carreira,S.Han,R.Agarwal,S.Ratnasamy, and S. Shenker. Network requirements for resource disaggregation. In Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation, OSDI'16, page 249–264, USA, 2016. USENIX Association. [13] J. Gu, Y. Lee, Y. Zhang, M. Chowdhury, and K. G. Shin. Efficient memory disaggregation with infiniswap. In Proceedings of the 14th USENIX Conference on Networked Systems Design and Implementation, NSDI’17, page 649–667, USA, 2017. USENIX Association. [14] INFINIBAND TRADE ASSOCIATION. Supplement to InfiniBand Architecture Specification Volume1 Release 1.2.2 Annex A16: RDMA over Converged Ethernet (RoCE). 2010. [15] A.Kalia, M.Kaminsky, and D.G.Andersen. Using RDMA efficiently for KeyValue services. SIGCOMM Comput. Commun. Rev., 44(4):295–306, Aug. 2014. [16] A.Kalia, M.Kaminsky, and D.G.Andersen. Design guidelines for high performance RDMA systems. In Proceedings of the 2016 USENIX Conference on Usenix Annual Technical Conference, USENIX ATC ’16, page 437–450, USA, 2016. USENIX Association. [17] U. Kang, H. soo Yu, C. Park, H. Zheng, J. Halbert, K. Bains, S.J. Jang, and J.S.Choi. Coarchitecting controllers and dram to enhance dram process scaling. 2014. [18] A. LagarCavilla, J. Ahn, S. Souhlal, N. Agarwal, R. Burny, S. Butt, J. Chang, A. Chaugule, N. Deng, J. Shahid, G. Thelen, K. A. Yurtsever, Y. Zhao, and P. Ranganathan. Softwaredefinedfar memoryin warehousescalecomputers. InProceedings of the TwentyFourth International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS ’19, page 317–330, New York, NY, USA, 2019. Association for Computing Machinery. [19] S.H. Lee. Technology scaling challenges and opportunities of memory devices. In 2016 IEEE International Electron Devices Meeting (IEDM), pages 1.1.1–1.1.8, 2016. [20] S. Liang, R. Noronha, and D. K. Panda. Swapping to remote memory over infiniband: An approach using a high performance network block device. In 2005 IEEE International Conference on Cluster Computing, pages 1–10, 2005. [21] O. Mutlu. Chapter 6 main memory scaling : Challenges and solution directions. 2015. [22] J. Nelson, B. Holt, B. Myers, P. Briggs, L. Ceze, S. Kahan, and M. Oskin. Latencytolerant software distributed shared memory. In Proceedings of the 2015 USENIX Conference on Usenix Annual Technical Conference,USENIXATC’15, page291–305, USA, 2015. USENIX Association. [23] A. Ousterhout, J. Fried, J. Behrens, A. Belay, and H. Balakrishnan. Shenango: Achieving high CPU efficiency for latencysensitive datacenter workloads. In J. R. Lorch and M. Yu, editors, 16th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2019, Boston, MA, February 2628, 2019, pages 361–378. USENIX Association, 2019. [24] Z.Ruan, M.Schwarzkopf, M.K.Aguilera, andA.Belay. AIFM:Highperformance, applicationintegrated far memory. In 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20), pages 315–332. USENIX Association, Nov. 2020. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81770 | - |
| dc.description.abstract | 近年來，隨著資料密集型工作被廣泛應用和記憶體製造技術進步幅度趨緩的影響，如何有效率得使用記憶體資源來最佳化系統效能是值得我們關注的議題。得益於近年來高速網路和遠端直接記憶體存取的發展，讓可組合記憶體變得可行。藉由把一台機器內未使用的記憶體借給其他機器使用，可以提高資料中心內整體記憶體的使用率，而本篇論文所研究的應用感知記憶體(AIFM)即是用軟體支援的方式，實現可組合記憶體。我們針對AIFM的進行效能量測，發現了其因為使用TCP/IP傳輸資料的關係，在多個客戶端同時使用遠端記憶體時，會有效能低落的問題。針對這個問題我們提出了用遠端記憶體直接存取（RDMA）取代TCP/IP的方式來降低提供遠端記憶體機器的負載。此外，為了解決RDMA在實作湊雜表會遇到需要多次遠端讀取的問題，我們也實作了結合TCP和RDMA的AIFM版本，其對原本RDMA版本的AIFM有1.5到2倍的加速。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T09:27:05Z (GMT). No. of bitstreams: 1 U0001-0410202113524000.pdf: 1702386 bytes, checksum: 71cbb327ef261651db7a9a5f0e1271f9 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | Contents 摘要 i Abstract ii 1 Introduction 1 2 Background and Related Work 4 2.1 Remote Memory Systems . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Remote Direct Memory Access . . . . . . . . . . . . . . . . . . . . . . . 5 2.3 ApplicationIntegrated Far Memory . . . . . . . . . . . . . . . . . . . . 6 2.4 Performance Issues for AIFM . . . . . . . . . . . . . . . . . . . . . . . 8 2.5 Related Works for Utilizing Remote Memory . . . . . . . . . . . . . . . 9 3 Methodology 11 3.1 The Proposed Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.1.1 The Original AIFM Workflow . . . . . . . . . . . . . . . . . . . 11 3.1.2 The Proposed Modifications . . . . . . . . . . . . . . . . . . . . 13 3.2 The Proposed RDMA Device . . . . . . . . . . . . . . . . . . . . . . . . 13 3.3 Accessing Hash Tables with RDMA . . . . . . . . . . . . . . . . . . . . 16 4 Evaluation 19 4.1 Endtoend Performance . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.1.1 Request Handling Latency . . . . . . . . . . . . . . . . . . . . . 20 4.1.2 Throughput . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.2 Performance Breakdown . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.2.1 Scalability on the Memory Node . . . . . . . . . . . . . . . . . . 23 4.2.2 CPU Utilization on the Compute Node . . . . . . . . . . . . . . 24 4.2.3 Latency of Accessing Remote Objects . . . . . . . . . . . . . . . 25 5 Conclusion 27 Bibliography 28 | |
| dc.language.iso | en | |
| dc.subject | 遠端記憶體直接存取 | zh_TW |
| dc.subject | 應用感知遠端記憶體 | zh_TW |
| dc.subject | 可組合記憶體 | zh_TW |
| dc.subject | RDMA | en |
| dc.subject | memory disaggregation | en |
| dc.subject | AIFM | en |
| dc.subject | TCP/IP | en |
| dc.title | 以RDMA加速應用感知遠端記憶體 | zh_TW |
| dc.title | Accelerating Application-Integrated Far Memory with RDMA | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 郭大維(Hsin-Tsai Liu),施吉昇(Chih-Yang Tseng),張原豪,梁文耀 | |
| dc.subject.keyword | 遠端記憶體直接存取,可組合記憶體,應用感知遠端記憶體, | zh_TW |
| dc.subject.keyword | TCP/IP,RDMA,AIFM,memory disaggregation, | en |
| dc.relation.page | 31 | |
| dc.identifier.doi | 10.6342/NTU202103529 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2021-10-05 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| Appears in Collections: | 資訊工程學系 | |
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| File | Size | Format | |
|---|---|---|---|
| U0001-0410202113524000.pdf Restricted Access | 1.66 MB | Adobe PDF |
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