Modern networks used for integrating custom Internet of Things (IoT) systems and devices
have restrictions and requirements unique to their individual applications. These application …

Given that the increasing rate of network bandwidth is far ahead of that of the compute
capacity of host CPU, which by default processes network packets, SmartNIC has been …

Vector search has emerged as the foundation for large-scale information retrieval and
machine learning systems, with search engines like Google and Bing processing tens of …

We present FleetRec, a high-performance and scalable recommendation inference system
within tight latency constraints. FleetRec takes advantage of heterogeneous hardware …

Communication switches have sometimes been augmented to process collectives, eg, in the
IBM BlueGene and Mellanox SHArP switches. In this work, we find that there is a great …

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

Data analysts often need to characterize a data stream as a first step to its further
processing. Some of the initial insights to be gained include, eg, the cardinality of the data …

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

Trends in hardware, the prevalence of the cloud, and the rise of highly demanding
applications have ushered an era of specialization that is quickly changing the way data is …

Deep neural networks are widely used in personalized recommendation systems. Such
models involve two major components: the memory-bound embedding layer and the …