As a recent innovation, network functions virtualization (NFV)—with its core concept of
replacing hardware middleboxes with software network functions (NFs) implemented in …

The increasing demand for cloud-based inference services requires the use of Graphics
Processing Unit (GPU). It is highly desirable to utilize GPU efficiently by multiplexing different …

We investigate the use of SmartNIC-accelerated servers to execute microservice-based
applications in the data center. By offloading suitable microservices to the SmartNIC's low …

Containers are widely used for resource management in datacenters. A common practice to
support deep learning (DL) training in container clouds is to statically bind GPUs to …

We present Heimdall, a mobile GPU coordination platform for emerging Augmented Reality
(AR) applications. Future AR apps impose an explored challenging workload: i) concurrent …

With rising network rates, cloud vendors increasingly deploy FPGA-based SmartNICs (F-
NICs), leveraging their inline processing capabilities to offload hypervisor networking …

GPU computing is becoming increasingly more popular with the proliferation of deep
learning (DL) applications. However, unlike traditional resources such as CPU or the …

We present PacketMill, a system for optimizing software packet processing, which (i)
introduces a new model to efficiently manage packet metadata and (ii) employs code …

Context Deep learning has achieved remarkable progress in various domains. However,
like any software system, deep learning systems contain bugs, some of which can have …

Unlike traditional resources such as CPU or the network, modern GPUs do not natively
support fine-grained sharing primitives. Consequently, implementing common policies such …