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20132025
most citedScaling Distributed Machine Learning with In-Network Aggregation

117 citations · 411 across the 25 of their papers we have counts for

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9 papers · 1 filter

cs.DC2021★ 3 cited

With Great Freedom Comes Great Opportunity: Rethinking Resource Allocation for Serverless Functions

Muhammad Bilal, Marco Canini, Rodrigo Fonseca +1

Current serverless offerings give users a limited degree of flexibility for configuring the resources allocated to their function invocations by either coupling memory and CPU reso…

cs.DC2021★ 1 cited

RDMA is Turing complete, we just did not know it yet!

Waleed Reda, Marco Canini, Dejan Kostić +1

It is becoming increasingly popular for distributed systems to exploit offload to reduce load on the CPU. Remote Direct Memory Access (RDMA) offload, in particular, has become popu…

cs.DC2019

On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning

Aritra Dutta, El Houcine Bergou, Ahmed M. Abdelmoniem +4

Compressed communication, in the form of sparsification or quantization of stochastic gradients, is employed to reduce communication costs in distributed data-parallel training of…

cs.DC2019★ 8 cited

Assise: Performance and Availability via NVM Colocation in a Distributed File System

Thomas E. Anderson, Marco Canini, Jongyul Kim +6

The adoption of very low latency persistent memory modules (PMMs) upends the long-established model of disaggregated file system access. Instead, by colocating computation and PMM…

cs.DC2019★ 117 cited

Scaling Distributed Machine Learning with In-Network Aggregation

Amedeo Sapio, Marco Canini, Chen-Yu Ho +7

Training machine learning models in parallel is an increasingly important workload. We accelerate distributed parallel training by designing a communication primitive that uses a p…

cs.DC2019

Partitioned Paxos via the Network Data Plane

Huynh Tu Dang, Pietro Bressana, Han Wang +6

Consensus protocols are the foundation for building fault-tolerant, distributed systems, and services. They are also widely acknowledged as performance bottlenecks. Several recent…

cs.DC2016★ 8 cited

Network Hardware-Accelerated Consensus

Huynh Tu Dang, Pietro Bressana, Han Wang +5

Consensus protocols are the foundation for building many fault-tolerant distributed systems and services. This paper posits that there are significant performance benefits to be ga…

cs.DC2015

Paxos Made Switch-y

Huynh Tu Dang, Marco Canini, Fernando Pedone +1

This paper describes an implementation of the well-known consensus protocol, Paxos, in the P4 programming language. P4 is a language for programming the behavior of network forward…

cs.DC2013★ 3 cited

A Distributed SDN Control Plane for Consistent Policy Updates

Marco Canini, Petr Kuznetsov, Dan Levin +1

Software-defined networking (SDN) is a novel paradigm that out-sources the control of packet-forwarding switches to a set of software controllers. The most fundamental task of thes…