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More Bang for the Buck: Superlinear Scaling with Distributed Self-Adjusting Systems (Invited Talk)

Authors Jonas Köppeler , Maciej Pacut , Tamás Lévai , Vamsi Addanki , Stefan Schmid , Gábor Rétvári

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Subject Classification

ACM Subject Classification
  • Networks → Network algorithms
  • Theory of computation → Design and analysis of algorithms
Keywords
  • self-adjusting systems
  • superlinear scaling
  • packet classification

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Abstract

Extracting maximum performance from a limited pool of parallel compute resources remains a central challenge. In this paper, we show an optimization technique that allows certain distributed systems to attain faster-than-linear (superlinear) performance improvement with only a linear scaling of the worker pool. Our insight is that (1) dispatching jobs to parallel workers so that the locality of reference in the workers' input increases and (2) implementing the workers with a self-adjusting algorithm to take advantage of the higher locality can yield superlinear scaling in many practical applications. First, we demonstrate our technique in simulations: by scaling textbook self-adjusting algorithms, we obtain 100-3,300x speedup using only 48 CPU cores - up to 70x beyond linear scaling. After that, we re-engineer the default Linux packet classifier to attain a 5-25x raw performance improvement as compared to the vanilla kernel. We demonstrate 800x speedup on synthetic traces and 220x speedup on real firewall traces with 32 CPU cores. Given these insights, we develop a formal model and a set of design guidelines to help understand the applicability of our optimization strategy for particular distributed system workloads.

Cite As Get BibTex

Jonas Köppeler, Maciej Pacut, Tamás Lévai, Vamsi Addanki, Stefan Schmid, and Gábor Rétvári. More Bang for the Buck: Superlinear Scaling with Distributed Self-Adjusting Systems (Invited Talk). In 5th Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 373, pp. 3:1-3:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.SAND.2026.3

Author Details

Jonas Köppeler
  • TU Berlin, Germany
Maciej Pacut
  • TU Berlin, Germany
Tamás Lévai
  • Budapest University of Technology and Economics, Hungary
Vamsi Addanki
  • Purdue University, West Lafayette, IN, USA
Stefan Schmid
  • TU Berlin, Germany
Gábor Rétvári
  • Budapest University of Technology and Economics, Hungary

Funding

European Research Council (ERC), Proof-of-Concept grant 101287293 (FortifyNet), 2026-2027.

Supplementary Materials

References

  1. Vamsi Addanki, Maciej Pacut, Arash Pourdamghani, Gabor Rétvári, Stefan Schmid, and Juan Vanerio. Self-adjusting partially ordered lists. In IEEE Conference on Computer Communications, IEEE INFOCOM, pages 1-10, 2023. Google Scholar
  2. Susanne Albers and Sonja Lauer. On list update with locality of reference. J. Comput. Syst. Sci., 82(5):627-653, 2016. URL: https://doi.org/10.1016/J.JCSS.2015.11.005.
  3. Carlos Alvarez, Jesus Corbal, and Mateo Valero. Fuzzy memoization for floating-point multimedia applications. IEEE Trans. Comput., 54(7):922-927, 2005. URL: https://doi.org/10.1109/TC.2005.119.
  4. Gene M. Amdahl. Validity of the single processor approach to achieving large scale computing capabilities. In Spring Joint Computer Conference, AFIPS '67 (Spring), pages 483-485. Association for Computing Machinery, 1967. URL: https://doi.org/10.1145/1465482.1465560.
  5. Gunnar Andersson. An approximation algorithm for max p-section. In STACS 99, 16th Annual Symposium on Theoretical Aspects of Computer Science, pages 237-247, 1999. URL: https://doi.org/10.1007/3-540-49116-3_22.
  6. Konstantin Andreev and Harald Räcke. Balanced graph partitioning. Theory Comput. Syst., 39(6):929-939, 2006. URL: https://doi.org/10.1007/S00224-006-1350-7.
  7. Samuel Arbesman, Jon M. Kleinberg, and Steven H. Strogatz. Superlinear scaling for innovation in cities. Phys. Rev. E, 79, 2009. Google Scholar
  8. Chen Avin, Marcin Bienkowski, Andreas Loukas, Maciej Pacut, and Stefan Schmid. Dynamic balanced graph partitioning. SIAM J. Discret. Math., 34(3):1791-1812, 2020. URL: https://doi.org/10.1137/17M1158513.
  9. Chen Avin, Kaushik Mondal, and Stefan Schmid. Dynamically optimal self-adjusting single-source tree networks. In LATIN 2020: Theoretical Informatics - Latin American Symposium, volume 12118 of Lecture Notes in Computer Science, pages 143-154, 2020. URL: https://doi.org/10.1007/978-3-030-61792-9_12.
  10. Songyuan Bai, Hao Zheng, Chen Tian, Xiaoliang Wang, Chang Liu, Xin Jin, Fu Xiao, Qiao Xiang, Wanchun Dou, and Guihai Chen. Unison: a parallel-efficient and user-transparent network simulation kernel. In European Conference on Computer Systems, EuroSys, pages 115-131, 2024. URL: https://doi.org/10.1145/3627703.3629574.
  11. Amotz Bar-Noy and Michael Lampis. Online maximum directed cut. J. Comb. Optim., 24(1):52-64, 2012. URL: https://doi.org/10.1007/S10878-010-9318-6.
  12. Tom Barbette, Georgios P. Katsikas, Gerald Q. Maguire, and Dejan Kostić. RSS++: load and state-aware receive side scaling. In International Conference on Emerging Networking Experiments And Technologies, ACM CoNEXT '19, pages 318-333, 2019. Google Scholar
  13. Tom Barbette, Erfan Wu, Dejan Kostić, Gerald Q. Maguire, Panagiotis Papadimitratos, and Marco Chiesa. Cheetah: a high-speed programmable load-balancer framework with guaranteed per-connection-consistency. IEEE/ACM Transactions on Networking, 30(1):354-367, 2022. URL: https://doi.org/10.1109/TNET.2021.3113370.
  14. G. Bell, J. Gray, and A. Szalay. Petascale computational systems. Computer, 39(1):110-112, 2006. URL: https://doi.org/10.1109/MC.2006.29.
  15. Jon Louis Bentley, Kenneth L. Clarkson, and David B. Levine. Fast linear expected-time algorithms for computing maxima and convex hulls. Algorithmica, 9(2):168-183, 1993. URL: https://doi.org/10.1007/BF01188711.
  16. Jon Louis Bentley, Daniel Dominic Sleator, Robert Endre Tarjan, and Victor K. Wei. A locally adaptive data compression scheme. Commun. ACM, 29(4):320-330, 1986. URL: https://doi.org/10.1145/5684.5688.
  17. Prosenjit Bose, Karim Douïeb, and Stefan Langerman. Dynamic optimality for skip lists and b-trees. In ACM-SIAM Symposium on Discrete Algorithms, SODA, pages 1106-1114, 2008. URL: http://dl.acm.org/citation.cfm?id=1347082.1347203.
  18. Daniel Brahneborg, Wasif Afzal, Adnan Čaušević, and Mats Björkman. Superlinear and bandwidth friendly geo-replication for store-and-forward systems. In Proceedings of the 15th International Conference on Software Technologies (ICSOFT), pages 328-338. SciTePress, 2020. URL: https://doi.org/10.5220/0009835403280338.
  19. Brendan Burns. Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Services. O'Reilly Media, Inc., 1st edition, 2018. Google Scholar
  20. Kirk W. Cameron and Rong Ge. Generalizing Amdahl’s Law for power and energy. Computer, 45(3):75-77, 2012. URL: https://doi.org/10.1109/MC.2012.92.
  21. Rohit Chandra, Anoop Gupta, and John L. Hennessy. Data locality and load balancing in COOL. In Proceedings of the Fourth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP '93, pages 249-259. Association for Computing Machinery, 1993. URL: https://doi.org/10.1145/155332.155358.
  22. F. Chang, Wu chang Feng, and Kang Li. Approximate caches for packet classification. In IEEE INFOCOM, volume 4, pages 2196-2207, 2004. Google Scholar
  23. Daniel E. Eisenbud, Cheng Yi, Carlo Contavalli, Cody Smith, Roman Kononov, Eric Mann-Hielscher, Ardas Cilingiroglu, Bin Cheyney, Wentao Shang, and Jinnah Dylan Hosein. Maglev: a fast and reliable software network load balancer. In 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16), pages 523-535, March 2016. URL: https://www.usenix.org/conference/nsdi16/technical-sessions/presentation/eisenbud.
  24. Paul Emmerich, Sebastian Gallenmüller, Daniel Raumer, Florian Wohlfart, and Georg Carle. MoonGen: A Scriptable High-Speed Packet Generator. In Internet Measurement Conference 2015 (IMC'15), Tokyo, Japan, October 2015. Google Scholar
  25. V Faber, O M Lubeck, and A B White. Superlinear speedup of an efficient sequential algorithm is not possible. Parallel Comput., 3(3):259-260, 1986. URL: https://doi.org/10.1016/0167-8191(86)90024-4.
  26. Brad Fitzpatrick. Distributed caching with memcached. Linux J., 2004(124):5, 2004. Google Scholar
  27. Joshua Fried, Gohar Irfan Chaudhry, Enrique Saurez, Esha Choukse, Inigo Goiri, Sameh Elnikety, Rodrigo Fonseca, and Adam Belay. Making kernel bypass practical for the cloud with junction. In 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24), pages 55-73. USENIX Association, 2024. URL: https://www.usenix.org/conference/nsdi24/presentation/fried.
  28. A. Frieze and M. Jerrum. Improved approximation algorithms for MAX k-CUT and MAX BISECTION. In Algorithmica 18, pages 67-81, 1997. Google Scholar
  29. Hamid Ghasemirahni, Tom Barbette, Georgios P. Katsikas, Alireza Farshin, Amir Roozbeh, Massimo Girondi, Marco Chiesa, Gerald Q. Maguire Jr., and Dejan Kostić. Packet order matters! improving application performance by deliberately delaying packets. In USENIX Symposium on Networked Systems Design and Implementation (NSDI), pages 807-827, 2022. URL: https://www.usenix.org/conference/nsdi22/presentation/ghasemirahni.
  30. Yoann Ghigoff, Julien Sopena, Kahina Lazri, Antoine Blin, and Gilles Muller. BMC: accelerating memcached using safe in-kernel caching and pre-stack processing. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21), pages 487-501, 2021. URL: https://www.usenix.org/conference/nsdi21/presentation/ghigoff.
  31. hashicorp/btree. URL: https://pkg.go.dev/github.com/google/btree.
  32. golang-collections/collections. URL: https://pkg.go.dev/github.com/golang-collections/collections#readme-splay-tree.
  33. hashicorp/golang-lru. URL: https://pkg.go.dev/github.com/hashicorp/golang-lru/v2.
  34. Neil Gunther. Superlinear scalability. In Symposium and Bootcamp on the Science of Security, HotSoS '13, 2013. Google Scholar
  35. Neil Gunther, Paul Puglia, and Kristofer Tomasette. Hadoop superlinear scalability: The perpetual motion of parallel performance. Queue, 13(5):20-42, 2015. Google Scholar
  36. Neil J. Gunther. A general theory of computational scalability based on rational functions, 2008. URL: https://arxiv.org/abs/0808.1431.
  37. Neil J. Gunther. Guerrilla Capacity Planning: A Tactical Approach to Planning for Highly Scalable Applications and Services. Springer Publishing Company, Incorporated, 1st edition, 2010. Google Scholar
  38. P. Gupta and N. McKeown. Classifying packets with hierarchical intelligent cuttings. IEEE Micro, 20(1):34-41, 2000. URL: https://doi.org/10.1109/40.820051.
  39. Pankaj Gupta and Nick McKeown. Algorithms for packet classification. IEEE Network, 15(2):24-32, 2001. URL: https://doi.org/10.1109/65.912717.
  40. Marjan Gusev and Sasko Ristov. Superlinear speedup in Windows Azure cloud. In IEEE International Conference on Cloud Networking (CLOUDNET), pages 173-175, 2012. URL: https://doi.org/10.1109/CLOUDNET.2012.6483679.
  41. J.L. Gustafson. Fixed time, tiered memory, and superlinear speedup. In Distributed Memory Computing Conference, volume 2, pages 1255-1260, 1990. Google Scholar
  42. John L. Gustafson. Reevaluating Amdahl’s Law. Commun. ACM, 31(5):532-533, May 1988. URL: https://doi.org/10.1145/42411.42415.
  43. R Haas. Scalability, in graphical form, analyzed. http://rhaas.blogspot.com/2011/09/scalability-in-graphical-form-analyzed.html, 2011.
  44. Heiko Hamann. Superlinear scalability in parallel computing and multi-robot systems: Shared resources, collaboration, and network topology. In Architecture of Computing Systems (ARCS 2018), pages 31-42. Springer, 2018. URL: https://doi.org/10.1007/978-3-319-77610-1_3.
  45. D.P. Helmbold and C.E. McDowell. Modelling speedup (n) greater than n. IEEE Transactions on Parallel and Distributed Systems, 1(2):250-256, 1990. URL: https://doi.org/10.1109/71.80148.
  46. James H. Hester and Daniel S. Hirschberg. Self-organizing linear search. ACM Comput. Surv., 17(3):295-311, 1985. URL: https://doi.org/10.1145/5505.5507.
  47. Mark D. Hill and Michael R. Marty. Amdahl’s Law in the multicore era. Computer, 41(7):33-38, 2008. URL: https://doi.org/10.1109/MC.2008.209.
  48. Haiyang Jiang, Guangxing Zhang, Gaogang Xie, Kavé Salamatian, and Laurent Mathy. Scalable high-performance parallel design for network intrusion detection systems on many-core processors. In Symposium on Architectures for Networking and Communications Systems, ACM/IEEE ANCS, pages 137-146, 2013. URL: https://doi.org/10.1109/ANCS.2013.6665196.
  49. Douglas W. Jones. Application of splay trees to data compression. Communications of the ACM, 31(8):996-1007, 1988. URL: https://doi.org/10.1145/63030.63036.
  50. Murad Kablan, Azzam Alsudais, Eric Keller, and Franck Le. Stateless network functions: Breaking the tight coupling of state and processing. In USENIX Conference on Networked Systems Design and Implementation, NSDI'17, pages 97-112, 2017. URL: https://www.usenix.org/conference/nsdi17/technical-sessions/presentation/kablan.
  51. Georgios P. Katsikas, Tom Barbette, Dejan Kostić, Rebecca Steinert, and Gerald Q. Maguire Jr. Metron: NFV service chains at the true speed of the underlying hardware. In 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18), pages 171-186, April 2018. URL: https://www.usenix.org/conference/nsdi18/presentation/katsikas.
  52. Peyman Kazemian, George Varghese, and Nick McKeown. Header space analysis: Static checking for networks. In Symposium on Networked Systems Design and Implementation, USENIX NSDI, pages 113-126, 2012. URL: https://www.usenix.org/conference/nsdi12/technical-sessions/presentation/kazemian.
  53. Kirill Kogan, Sergey Nikolenko, Ori Rottenstreich, William Culhane, and Patrick Eugster. SAX-PAC (Scalable And EXpressive PAcket Classification). In Conference of the ACM Special Interest Group on Data Communication, SIGCOMM '14, pages 15-26, 2014. URL: https://doi.org/10.1145/2619239.2626294.
  54. S. Krishnaprasad. Uses and abuses of Amdahl’s Law. J. Comput. Sci. Coll., 17(2):288-293, December 2001. URL: https://doi.org/10.5555/775339.775386.
  55. Jason Lei and Vishal Shrivastav. Seer: Enabling Future-Aware online caching in networked systems. In USENIX Symposium on Networked Systems Design and Implementation (NSDI), pages 635-649, 2024. URL: https://www.usenix.org/conference/nsdi24/presentation/lei.
  56. Tamás Lévai, Felicián Németh, Barath Raghavan, and Gabor Retvari. Batchy: batch-scheduling data flow graphs with service-level objectives. In USENIX Symposium on Networked Systems Design and Implementation (NSDI), pages 633-649, 2020. Google Scholar
  57. Wenjun Li, Xianfeng Li, Hui Li, and Gaogang Xie. Cutsplit: A decision-tree combining cutting and splitting for scalable packet classification. In IEEE INFOCOM, pages 2645-2653, 2018. URL: https://doi.org/10.1109/INFOCOM.2018.8485947.
  58. Hyeontaek Lim, Dongsu Han, David G. Andersen, and Michael Kaminsky. MICA: A holistic approach to fast In-Memory Key-Value storage. In 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI 14), pages 429-444, April 2014. URL: https://www.usenix.org/conference/nsdi14/technical-sessions/presentation/lim.
  59. L. Linguaglossa, S. Lange, S. Pontarelli, G. Rétvári, D. Rossi, T. Zinner, R. Bifulco, M. Jarschel, and G. Bianchi. Survey of performance acceleration techniques for Network Function Virtualization. Proceedings of the IEEE, 107(4):746-764, 2019. URL: https://doi.org/10.1109/JPROC.2019.2896848.
  60. Tamás Lévai, Gergely Pongrácz, Péter Megyesi, Péter Vörös, Sándor Laki, Felicián Németh, and Gábor Rétvári. The price for programmability in the software data plane: The vendor perspective. IEEE Journal on Selected Areas in Communications, 36(12):2621-2630, 2018. URL: https://doi.org/10.1109/JSAC.2018.2871307.
  61. S. Mahajan and J. Ramesh. Derandomizing semidefinite programming based approximation algorithms. In Proc. 36th Ann. IEEE Symp. on Foundations of Comput. Sci. (FOCS), pages 162-169, 1995. Google Scholar
  62. Ami Marowka. Extending Amdahl’s Law for heterogeneous computing. In 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications, pages 309-316, 2012. URL: https://doi.org/10.1109/ISPA.2012.47.
  63. Jiří Matoušek, Gianni Antichi, Adam Lučanský, Andrew W. Moore, and Jan Kořenek. ClassBench-ng: recasting ClassBench after a decade of network evolution. In Symposium on Architectures for Networking and Communications Systems, IEEE/ACM ANCS, pages 204-216, 2017. Google Scholar
  64. Sebastiano Miano. sebymiano/pcap-utils. URL: https://github.com/sebymiano/pcap-utils.
  65. Sebastiano Miano, Alireza Sanaee, Fulvio Risso, Gábor Rétvári, and Gianni Antichi. Domain specific run time optimization for software data planes. In ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS '22, pages 1148-1164, 2022. URL: https://doi.org/10.1145/3503222.3507769.
  66. The nftables project. URL: https://wiki.nftables.org.
  67. Rajesh Nishtala, Hans Fugal, Steven Grimm, Marc Kwiatkowski, Herman Lee, Harry C. Li, Ryan McElroy, Mike Paleczny, Daniel Peek, Paul Saab, David Stafford, Tony Tung, and Venkateshwaran Venkataramani. Scaling memcache at Facebook. In 10th USENIX Symposium on Networked Systems Design and Implementation (NSDI 13), pages 385-398, April 2013. URL: https://www.usenix.org/conference/nsdi13/technical-sessions/presentation/nishtala.
  68. Vladimir Olteanu, Alexandru Agache, Andrei Voinescu, and Costin Raiciu. Stateless datacenter load-balancing with Beamer. In 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18), pages 125-139, 2018. Google Scholar
  69. ONF. Openflow reference release. https://github.com/mininet/openflow, 2013.
  70. I. Onyuksel and S.H. Hosseini. Amdahl’s law: a generalization under processor failures. IEEE Transactions on Reliability, 44(3):455-462, 1995. URL: https://doi.org/10.1109/24.406581.
  71. Shoumik Palkar, Chang Lan, Sangjin Han, Keon Jang, Aurojit Panda, Sylvia Ratnasamy, Luigi Rizzo, and Scott Shenker. E2: a framework for NFV applications. In Symposium on Operating Systems Principles, SOSP '15, pages 121-136, 2015. URL: https://doi.org/10.1145/2815400.2815423.
  72. Eunhui Park and David M. Mount. A self-adjusting data structure for multidimensional point sets. In Algorithms - ESA Annual European Symposium, volume 7501, pages 778-789, 2012. URL: https://doi.org/10.1007/978-3-642-33090-2_67.
  73. Ben Pfaff, Justin Pettit, Teemu Koponen, Ethan Jackson, Andy Zhou, Jarno Rajahalme, Jesse Gross, Alex Wang, Joe Stringer, Pravin Shelar, Keith Amidon, and Martin Casado. The design and implementation of Open vSwitch. In 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI 15), pages 117-130, 2015. URL: https://www.usenix.org/conference/nsdi15/technical-sessions/presentation/pfaff.
  74. Sasko Ristov, Radu Prodan, Marjan Gusev, and Karolj Skala. Superlinear speedup in HPC systems: Why and when? In Federated Conference on Computer Science and Information Systems (FedCSIS), pages 889-898, 2016. URL: https://doi.org/10.15439/2016F498.
  75. Ori Rottenstreich and János Tapolcai. Optimal rule caching and lossy compression for longest prefix matching. IEEE/ACM Transactions on Networking, 25(2):864-878, 2016. URL: https://doi.org/10.1109/TNET.2016.2611482.
  76. Scaling in the linux networking stack. URL: https://www.kernel.org/doc/Documentation/networking/scaling.txt.
  77. Packet classification and access control. URL: https://doc.dpdk.org/guides/prog_guide/packet_classif_access_ctrl.html.
  78. Amedeo Sapio, Marco Canini, Chen-Yu Ho, Jacob Nelson, Panos Kalnis, Changhoon Kim, Arvind Krishnamurthy, Masoud Moshref, Dan Ports, and Peter Richtarik. Scaling distributed machine learning with In-Network aggregation. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21), pages 785-808, 2021. URL: https://www.usenix.org/conference/nsdi21/presentation/sapio.
  79. Chris Sears. The elements of cache programming style. In 4th Annual Linux Showcase & Conference (ALS 2000). USENIX Association, 2000. URL: https://www.usenix.org/conference/als-2000/elements-cache-programming-style.
  80. Sdn analytics and control: Superlinear. https://blog.sflow.com/2010/09/superlinear.html, 2010.
  81. Justine Sherry. The I/O driven server: From SmartNICs to data movement controllers. Computer Communications Review (CCR), 53(3), 2023. URL: https://doi.org/10.1145/3649171.3649174.
  82. Sumeet Singh, Florin Baboescu, George Varghese, and Jia Wang. Packet classification using multidimensional cutting. In Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, pages 213-224, 2003. URL: https://doi.org/10.1145/863955.863980.
  83. Daniel D. Sleator and Robert E. Tarjan. Amortized efficiency of list update and paging rules. Commun. ACM, 28(2):202-208, February 1985. URL: https://doi.org/10.1145/2786.2793.
  84. Daniel Dominic Sleator and Robert Endre Tarjan. Self-adjusting binary search trees. J. ACM, 32(3):652-686, 1985. URL: https://doi.org/10.1145/3828.3835.
  85. Chen Sun, Jun Bi, Zhilong Zheng, Heng Yu, and Hongxin Hu. Nfp: Enabling network function parallelism in nfv. In Conference of the ACM Special Interest Group on Data Communication, SIGCOMM '17, pages 43-56, 2017. URL: https://doi.org/10.1145/3098822.3098826.
  86. Herb Sutter. Going superlinear. Dr. Dobb’s J., 2008. URL: https://www.drdobbs.com/cpp/going-superlinear/206100542.
  87. Herb Sutter. Super linearity and the bigger machine. Dr. Dobb’s J., 2008. URL: https://www.drdobbs.com/parallel/super-linearity-and-the-bigger-machine/206903306.
  88. David E. Taylor and Jonathan S. Turner. ClassBench: a packet classification benchmark. IEEE/ACM Transactions on Networking, 15(3):499-511, 2007. URL: https://doi.org/10.1145/1295237.1295239.
  89. William Tu, Yi-Hung Wei, Gianni Antichi, and Ben Pfaff. Revisiting the Open VSwitch Dataplane ten years later. In Conference of the ACM Special Interest Group on Data Communication, SIGCOMM '21, pages 245-257, 2021. URL: https://doi.org/10.1145/3452296.3472914.
  90. Balajee Vamanan, Gwendolyn Voskuilen, and T. N. Vijaykumar. EffiCuts: optimizing packet classification for memory and throughput. In Conference of the ACM Special Interest Group on Data Communication, SIGCOMM '10, pages 207-218, 2010. URL: https://doi.org/10.1145/1851182.1851208.
  91. Wikipedia. Speedup: Super-linear speedup. URL: https://en.wikipedia.org/wiki/Speedup#Super-linear_speedup.
  92. Shinae Woo, Justine Sherry, Sangjin Han, Sue Moon, Sylvia Ratnasamy, and Scott Shenker. Elastic scaling of stateful network functions. In USENIX Conference on Networked Systems Design and Implementation, NSDI'18, pages 299-312, 2018. URL: https://www.usenix.org/conference/nsdi18/presentation/woo.
  93. Haoran Zhang, Konstantinos Kallas, Spyros Pavlatos, Rajeev Alur, Sebastian Angel, and Vincent Liu. MuCache: A general framework for caching in microservice graphs. In USENIX Symposium on Networked Systems Design and Implementation (NSDI), pages 221-238, 2024. URL: https://www.usenix.org/conference/nsdi24/presentation/zhang-haoran.
  94. Yazhuo Zhang, Juncheng Yang, Yao Yue, Ymir Vigfusson, and K.V. Rashmi. SIEVE is simpler than LRU: an efficient Turn-Key eviction algorithm for web caches. In USENIX Symposium on Networked Systems Design and Implementation (NSDI), pages 1229-1246, 2024. Google Scholar
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