Related papers: NetRPC: Enabling In-Network Computation in Remote …

The most of computing environments in the IT support organization like NIC are designed to run in centralized datacentre. The centralized infrastructure of various development projects are used to deploy their services on it and connecting…

This paper presents a new communication interface for the DareFightingICE platform, a Java-based fighting game focused on implementing AI for controlling a non-player character. The interface uses an open-source remote procedure call, gRPC…

We design a cross-layer approach to aid in develop- ing a cooperative solution using multi-packet reception (MPR), network coding (NC), and medium access (MAC). We construct a model for the behavior of the IEEE 802.11 MAC protocol and apply…

Random Linear Network Coding (RLNC) has emerged as a powerful tool for robust high-throughput multicast. Projection analysis - a recently introduced technique - shows that the distributed packetized RLNC protocol achieves (order) optimal…

Microservices are a promising technology for future networks, and many research efforts have been devoted to optimally placing microservices in cloud data centers. However, microservices deployment in edge and in-network devices is more…

In recent years, the research community has raised serious questions about the reproducibility of scientific work. In particular, since many studies include some kind of computing work, reproducibility is also a technological challenge, not…

The tremendous advancements in the Internet of Things (IoT) increasingly involve computationally intensive services. These services often require more computation resources than can entirely be satisfied on local IoT devices. Cloud…

Interprocess communication, IPC, is one of the most fundamental functions of a modern operating system, playing an essential role in the fabric of contemporary applications. This report conducts an investigation in FreeBSD of the real world…

The network interface adapter (NIC) is a critical component of a cloud server occupying a unique position. Not only is network performance vital to efficient operation of the machine, but unlike compute accelerators like GPUs, the network…

Emerging applications such as augmented reality and tactile Internet are compute-intensive and latency-sensitive, which hampers their running in constrained end devices alone or in the distant cloud. The stringent requirements of such…

High-throughput computing projects require the solution of large numbers of problems. In many cases, these problems can be solved on desktop PCs, or can be broken down into independent "PC-solvable" sub-problems. In such cases, the projects…

Secure Multi-party Computation (MPC) enables untrusted parties to jointly compute a function without revealing their inputs. Its application to machine learning (ML) has gained significant attention, particularly for secure inference…

Nowadays, the number of emerging embedded systems rapidly grows in many application domains, due to recent advances in artificial intelligence and internet of things. The main inherent specification of these application-specific systems is…

Neural networks are increasingly used in real-time systems, such as automated driving applications. This requires high-performance hardware with predictable timing behavior. State-of-the-art real-time hardware is limited in memory and…

A physical neural network (PNN) has both the strong potential to solve machine learning tasks and intrinsic physical properties, such as high-speed computation and energy efficiency. Reservoir computing (RC) is an excellent framework for…

Spawning duplicate requests, called cloning, is a powerful technique to reduce tail latency by masking service-time variability. However, traditional client-based cloning is static and harmful to performance under high load, while a recent…

The MultiNoC system implements a programmable on-chip multiprocessing platform built on top of an efficient, low area overhead intra-chip interconnection scheme. The employed interconnection structure is a Network on Chip, or NoC. NoCs are…

Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems, but requires computationally expensive online optimization. This paper studies approximations of such MPC controllers via neural…

Deep neural networks generate and process large volumes of data, posing challenges for low-resource embedded systems. In-memory computing has been demonstrated as an efficient computing infrastructure and shows promise for embedded AI…

Distributed data structures are key to implementing scalable applications for scientific simulations and data analysis. In this paper we look at two implementation styles for distributed data structures: remote direct memory access (RDMA)…