We propose a parameter server framework for distributed machine learning problems. Both
data and workloads are distributed over worker nodes, while the server nodes maintain …

Coordination services are a fundamental building block of modern cloud systems, providing
critical functionalities like configuration management and distributed locking. The major …

This paper describes a third-generation parameter server framework for distributed machine
learning. This framework offers two relaxations to balance system performance and …

Choosing a cloud storage system and specific operations for reading and writing data
requires developers to make decisions that trade off consistency for availability and …

Storage systems in data centers are an important component of large-scale online services.
They typically perform replicated transactional operations for high data availability and …

Responding to the" datacenter tax" and" killer microseconds" problems for memory-intensive
datacenter applications, diverse solutions including Smart NIC-based ones have been …

Data structures for non-volatile memories have to be designed such that they can be
atomically modified using transactions. Existing atomicity methods require data to be copied …

Distributed storage employs replication to mask failures and improve availability. However,
these systems typically exhibit a hard tradeoff between consistency and performance …

Some embodiments of the invention provide a forwarding element that has a data-plane
circuit (data plane) that can be configured to implement one or more load balancers. The …

Network traffic typically traverses a sequence of middleboxes forming a service function
chain, or simply a chain. Tolerating failures when they occur along chains is imperative to …