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This paper investigates distributed computing systems where computations are split into "Map" and "Reduce" functions.
J. Dean and S. Ghemawat, “MapReduce: Simplified data processing on large clusters,” Sixth USENIX OSDI , Dec. 2004
2004
Earlier work this paper cites.
M. Isard, M. Budiu, Y. Yu, A. Birrell, and D. Fetterly, “Dryad: distributed data-parallel programs from sequential building blocks,” in Proceedings of the 2nd ACM SIGOPS/EuroSys’07 , Mar. 2007
2007
Earlier work this paper cites.
S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “A unified coding framework for distributed computing with straggling servers,” in Proc. IEEE Globecom Works (GC Wkshps), Washington, DC, USA, pp. 1–6, 2016
2016
Earlier work this paper cites.
Q. Yu, S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “How to optimally allocate resources for coded distributed computing,” in Proc. IEEE Internation Conference on Communications (ICC), Paris, France, 21–25, May. 2017
2017
Cited alongside, same era.
S. Li, Q. Yu, M. A. Maddah-Ali, A. S. Avestimehr,“A scalable framework for wireless distributed computing,” IEEE/ACM Trans. Netw., vol. 25, no. 5, pp. 2643–2653, Oct. 2017
2017
Cited alongside, same era.
Y. H. Ezzeldin, M. Karmoose, and C. Fragouli, “Communication vs distributed computation: an alternative trade-off curve,” in Proc. IEEE Information Theory Workshop (ITW), Kaohsiung, Taiwan, pp. 279–283, Nov. 2017
2017
Cited alongside, same era.
Cited in the paper.
S. Li, M. A. Maddah-Ali, Q. Yu, and A. S. Avestimehr, “A fundamental tradeoff between computation and communication in distributed computing,” IEEE Trans. Inf. Theory, vol. 64, no. 1, pp. 109–128, Jan. 2018
2018
Closest in time.
K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding up distributed machine learning using codes,” IEEE Trans. Inf. Theory. vol. 64, no. 3, pp. 1514–1529, Mar. 2018
2018
Closest in time.
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