Memory is the most contended and least elastic resource in datacenter servers today.
Applications can use only local memory—which may be scarce—even though memory …

The microservice architecture is a popular software engineering approach for building
flexible, large-scale online services. Serverless functions, or function as a service (FaaS) …

Memory disaggregation has attracted great attention recently because of its benefits in
efficient memory utilization and ease of management. So far, memory disaggregation …

Datacenter applications demand microsecond-scale tail latencies and high request rates
from operating systems, and most applications handle loads that have high variance over …

Datacenter systems and I/O devices now run at single-digit microsecond latencies, requiring
ns-scale operating systems. Traditional kernel-based operating systems impose an …

This paper presents our design and experience with a microkernel-inspired approach to
host networking called Snap. Snap is a userspace networking system that supports Google's …

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 …

Emerging hardware like persistent memory (PM) and high-speed NICs are promising to
build efficient key-value stores. However, we observe that the small-sized access pattern in …

RDMA is expected to be highly scalable: to perform well in large-scale data center networks
where packet losses are inevitable (ie, high network scalability), and to support a large …

Non-volatile memory and remote direct memory access (RDMA) provide extremely high
performance in storage and network hardware. However, existing distributed file systems …