SmartNICs have recently emerged as an appealing device for accelerating distributed
systems. However, there has not been a comprehensive characterization of SmartNICs, and …

This paper presents a solution to the challenge of mitigating carbon emissions from hosting
large-scale machine learning (ML) inference services. ML inference is critical to modern …

Graph neural network (GNN) has been widely applied in real-world applications, such as
product recommendation in e-commerce platforms and risk control in financial management …

The massive growth of machine learning-based applications and the end of Moore's law
have created a pressing need to redesign computing platforms. We propose Lightning, the …

Modern graphs exert colossal time and space pressure on graph analytics applications. In
2022, Facebook social graph reaches 2.91 billion users with trillions of edges. Many …

FPGAs are increasingly prevalent in cloud deployments, serving as Smart-NICs or network-
attached accelerators. To facilitate the development of distributed applications with FPGAs …

Today, we are seeing two trends in the data center. On the one hand, applications are
becoming more fine-grained, driven by the recent trend of serverless computing and …

Memory optimization kernel features, such as memory deduplication, are designed to
improve the overall efficiency of systems like datacenter servers, and they have proven to be …

The widespread deployment of storage disaggregation in the cloud has facilitated flexible
scaling and storage overprovisioning, allowing for high utilization of storage capacity and …

Cross-silo federated learning (FL) leverages homomorphic encryption (HE) to obscure the
model updates from the clients. However, HE poses the challenges of complex …