4 citations · 4 across the 2 of their papers we have counts for
5 papers
Scalable Graph Neural Network Training: The Case for Sampling
Marco Serafini, Hui Guan
Graph Neural Networks (GNNs) are a new and increasingly popular family of deep neural network architectures to perform learning on graphs. Training them efficiently is challenging…
Aion: Better Late than Never in Event-Time Streams
Sérgio Esteves, Gianmarco De Francisci Morales, Rodrigo Rodrigues +2
Processing data streams in near real-time is an increasingly important task. In the case of event-timestamped data, the stream processing system must promptly handle late events th…
PushdownDB: Accelerating a DBMS using S3 Computation
Xiangyao Yu, Matt Youill, Matthew Woicik +4
This paper studies the effectiveness of pushing parts of DBMS analytics queries into the Simple Storage Service (S3) engine of Amazon Web Services (AWS), using a recently released…
LiveGraph: A Transactional Graph Storage System with Purely Sequential Adjacency List Scans
Xiaowei Zhu, Guanyu Feng, Marco Serafini +5
The specific characteristics of graph workloads make it hard to design a one-size-fits-all graph storage system. Systems that support transactional updates use data structures with…
Scaling Out Acid Applications with Operation Partitioning
Habib Saissi, Marco Serafini, Neeraj Suri
OLTP applications with high workloads that cannot be served by a single server need to scale out to multiple servers. Typically, scaling out entails assigning a different partition…