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Prediction serving systems are designed to provide large volumes of low-latency inferences machine learning models.
First version of a data flow procedure language
J. B. Dennis · 1974
Earlier work this paper cites.
A preliminary architecture for a basic data-flow processor
J. B. Dennis and D. P. Misunas · 1974
Earlier work this paper cites.
Dynamic query optimization in rdb/vms
G. Antoshenkov · 1993
Earlier work this paper cites.
The click modular router
E. Kohler, R. Morris, B. Chen, J. Jannotti, and M. F. Kaashoek · 2000
Earlier work this paper cites.
Seda: an architecture for well-conditioned, scalable internet services
M. Welsh, D. Culler, and E. Brewer · 2001
Earlier work this paper cites.
Implementing declarative overlays
B. T. Loo, T. Condie, J. M. Hellerstein, P. Maniatis, T. Roscoe, and I. Stoica · 2005
Earlier work this paper cites.
Dryad: Distributed data-parallel programs from sequential building blocks
M. Isard, M. Budiu, Y. Yu, A. Birrell, and D. Fetterly · 2007
Earlier work this paper cites.
Mapreduce: simplified data processing on large clusters
J. Dean and S. Ghemawat · 2008
Earlier work this paper cites.
Variant-based competitive parallel execution of sequential programs
O. Trachsel and T. R. Gross · 2010
Earlier work this paper cites.
Consistency analysis in bloom: a calm and collected approach
P. Alvaro, N. Conway, J. M. Hellerstein, and W. R. Marczak · 2011
Earlier work this paper cites.
Autoscale: Dynamic, robust capacity management for multi-tier data centers
A. Gandhi, M. Harchol-Balter, R. Raghunathan, and M. A. Kozuch · 2012
Earlier work this paper cites.
Zeta: Scheduling interactive services with partial execution
Y. He, S. Elnikety, J. Larus, and C. Yan · 2012
Earlier work this paper cites.
Why it is time for a hype: A hybrid query processing engine for efficient gpu coprocessing in dbms
S. Breß and G. Saake · 2013
Earlier work this paper cites.
Nephele streaming: Stream processing under qos constraints at scale
B. Lohrmann, D. Warneke, and O. Kao · 2013
Earlier work this paper cites.
Naiad: A timely dataflow system
D. G. Murray, F. McSherry, R. Isaacs, M. Isard, P. Barham, and M. Abadi · 2013
Earlier work this paper cites.
P4: Programming protocol-independent packet processors
P. Bosshart, D. Daly, G. Gibb, M. Izzard, N. McKeown, J. Rexford, C. Schlesinger, D. Talayco, A. Vahdat, G. Varghese, et al · 2014
Earlier work this paper cites.
Apache flink: Stream and batch processing in a single engine
P. Carbone, A. Katsifodimos, S. Ewen, V. Markl, S. Haridi, and K. Tzoumas · 2015
Earlier work this paper cites.
Elastic stream processing with latency guarantees
B. Lohrmann, P. Janacik, and O. Kao · 2015
Earlier work this paper cites.
Lasp: A language for distributed, coordination-free programming
C. Meiklejohn and P. Van Roy · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al · 2015
Earlier work this paper cites.
C3: Cutting tail latency in cloud data stores via adaptive replica selection
L. Suresh, M. Canini, S. Schmid, and A. Feldmann · 2015
Cited alongside, same era.
Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna · 2015
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Serverless computation with openlambda
S. Hendrickson, S. Sturdevant, T. Harter, V. Venkataramani, A. C. Arpaci-Dusseau, and R. H. Arpaci-Dusseau · 2016
Cited alongside, same era.
Fasttext.zip: Compressing text classification models
A. Joulin, E. Grave, P. Bojanowski, M. Douze, H. Jégou, and T. Mikolov · 2016
Cited alongside, same era.
Applied machine learning at facebook: A datacenter infrastructure perspective
K. Hazelwood, S. Bird, D. Brooks, S. Chintala, U. Diril, D. Dzhulgakov, M. Fawzy, B. Jia, Y. Jia, A. Kalro, J. Law, K. Lee, J. Lu, P. Noordhuis, M. Smelyanskiy, L. Xiong, and X. Wang · 2018
Later among the works it cites.
Serverless computing: One step forward, two steps back
J. M. Hellerstein, J. Faleiro, J. E. Gonzalez, J. Schleier-Smith, V. Sreekanti, A. Tumanov, and C. Wu · 2018
Later among the works it cites.
Three steps is all you need: fast, accurate, automatic scaling decisions for distributed streaming dataflows
V. Kalavri, J. Liagouris, M. Hoffmann, D. Dimitrova, M. Forshaw, and T. Roscoe · 2018
Later among the works it cites.
Three steps is all you need: Fast, accurate, automatic scaling decisions for distributed streaming dataflows
V. Kalavri, J. Liagouris, M. Hoffmann, D. Dimitrova, M. Forshaw, and T. Roscoe · 2018
Later among the works it cites.
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A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov · 2016
Cited alongside, same era.
Mllib: Machine learning in apache spark
X. Meng, J. Bradley, B. Yavuz, E. Sparks, S. Venkataraman, D. Liu, J. Freeman, D. Tsai, M. Amde, S. Owen, et al · 2016
Cited alongside, same era.
Azureml: Anatomy of a machine learning service
A. Team · 2016
Cited alongside, same era.
Apache spark: A unified engine for big data processing
M. Zaharia, R. S. Xin, P. Wendell, T. Das, M. Armbrust, A. Dave, X. Meng, J. Rosen, S. Venkataraman, M. J. Franklin, A. Ghodsi, J. Gonzalez, S. Shenker, and I. Stoica · 2016
Cited alongside, same era.
Tfx: A tensorflow-based production-scale machine learning platform
D. Baylor, E. Breck, H.-T. Cheng, N. Fiedel, C. Y. Foo, Z. Haque, S. Haykal, M. Ispir, V. Jain, L. Koc, et al · 2017
Cited alongside, same era.
Drs: Auto-scaling for real-time stream analytics
T. Z. J. Fu, J. Ding, R. T. B. Ma, M. Winslett, Y. Yang, and Z. Zhang · 2017
Cited alongside, same era.
Convolutional sequence to sequence learning
J. Gehring, M. Auli, D. Grangier, D. Yarats, and Y. N. Dauphin · 2017
Cited alongside, same era.
J. Redmon and A. Farhadi · 2018
Later among the works it cites.
Deep interest network for click-through rate prediction
G. Zhou, X. Zhu, C. Song, Y. Fan, H. Zhu, X. Ma, Y. Yan, J. Jin, H. Li, and K. Gai · 2018
Later among the works it cites.
Taso: Optimizing deep learning computation with automatic generation of graph substitutions
Z. Jia, O. Padon, J. Thomas, T. Warszawski, M. Zaharia, and A. Aiken · 2019
Later among the works it cites.
Parity models: erasure-coded resilience for prediction serving systems
J. Kosaian, K. Rashmi, and S. Venkataraman · 2019
Later among the works it cites.
Parity models: Erasure-coded resilience for prediction serving systems
J. Kosaian, K. V. Rashmi, and S. Venkataraman · 2019
Later among the works it cites.
A tour of gallifrey, a language for geodistributed programming
M. Milano, R. Recto, T. Magrino, and A. C. Myers · 2019
Later among the works it cites.
fairseq: A fast, extensible toolkit for sequence modeling
M. Ott, S. Edunov, A. Baevski, A. Fan, S. Gross, N. Ng, D. Grangier, and M. Auli · 2019
Later among the works it cites.
Pytorch: An imperative style, high-performance deep learning library
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala · 2019
Later among the works it cites.
Archipelago: A scalable low-latency serverless platform
A. Singhvi, K. Houck, A. Balasubramanian, M. D. Shaikh, S. Venkataraman, and A. Akella · 2019
Later among the works it cites.
Anna: A kvs for any scale
C. Wu, J. Faleiro, Y. Lin, and J. Hellerstein · 2019
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Autoscaling tiered cloud storage in anna
C. Wu, V. Sreekanti, and J. M. Hellerstein · 2019
Later among the works it cites.
The architectural implications of facebook’s dnn-based personalized recommendation
U. Gupta, C.-J. Wu, X. Wang, M. Naumov, B. Reagen, D. Brooks, B. Cottel, K. Hazelwood, M. Hempstead, B. Jia, et al · 2020
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The remarkable utility of dataflow computing, 2020
M. Schwarzkopf · 2020
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M. Shahrad, R. Fonseca, Í. Goiri, G. Chaudhry, P. Batum, J. Cooke, E. Laureano, C. Tresness, M. Russinovich, and R. Bianchini · 2020
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Cloudburst: Stateful functions-as-a-service, 2020
V. Sreekanti, C. Wu, X. C. Lin, J. Schleier-Smith, J. M. Faleiro, J. E. Gonzalez, J. M. Hellerstein, and A. Tumanov · 2020
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