Purpose Big data is increasingly becoming a major organizational enterprise force to reckon
with in this global era for all sizes of industries. It is a trending new enterprise system or …

Programmable data plane technologies enable the systematic reconfiguration of the low-
level processing steps applied to network packets and are key drivers toward realizing the …

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

Distributed deep neural network training (DT) systems are widely deployed in clusters where
the network is shared across multiple tenants, ie, multiple DT jobs. Each DT job computes …

Programmable data plane hardware creates new opportunities for infusing intelligence into
the network. This raises a fundamental question: what kinds of computation should be …

There has been much research devoted to improving the performance of data analytics
frameworks, but comparatively little effort has been spent systematically identifying the …

Balanced graph partitioning in the streaming setting is a key problem to enable scalable and
efficient computations on massive graph data such as web graphs, knowledge graphs, and …

Big Data has become a very popular term. It refers to the enormous amount of structured,
semi-structured and unstructured data that are exponentially generated by high …

The emergence of programmable network devices and the increasing data traffic of
datacenters motivate the idea of in-network computation. By offloading compute operations …

Big data, with their promise to discover valuable insights for better decision making, have
recently attracted significant interest from both academia and industry. Voluminous data are …