Related papers: A Prediction Packetizing Scheme for Reducing Chann…

We propose an explicit rate indication scheme for congestion avoidance in ATM networks. In this scheme, the network switches monitor their load on each link, determining a load factor, the available capacity, and the number of currently…

In this paper we extend the concept of the traditional transactor, which focuses on correct content transfer, to a new timing-coherent transactor that also accurately aligns the timing of each transaction boundary so that designers can…

Particle tracking in large-scale numerical simulations of turbulent flows presents one of the major bottlenecks in parallel performance and scaling efficiency. Here, we describe a particle tracking algorithm for large-scale parallel…

Supporting the programming of stateful packet forwarding functions in hardware has recently attracted the interest of the research community. When designing such switching chips, the challenge is to guarantee the ability to program…

Packet-level discrete-event simulation (PLDES) is a prevalent tool for evaluating detailed performance of large model training. Although PLDES offers high fidelity and generality, its slow performance has plagued networking practitioners.…

This paper proposes several explicit and implicit multistep frequency response optimized integrators considering first or second order derivative. A prediction-based method aiming at accelerating a novel power system transient simulation…

Collision-free navigation in cluttered environments with static and dynamic obstacles is essential for many multi-robot tasks. Dynamic obstacles may also be interactive, i.e., their behavior varies based on the behavior of other entities.…

It is usually infeasible to fit and train an entire large deep neural network (DNN) model using a single edge device due to the limited resources. To facilitate intelligent applications across edge devices, researchers have proposed…

Radar sensing will be integrated into the 6G communication system to support various applications. In this integrated sensing and communication system, a radar target may also be a communication channel scatterer. In this case, the radar…

Traffic simulators are important tools for tasks such as urban planning and transportation management. Microscopic simulators allow per-vehicle movement simulation, but require longer simulation time. The simulation overhead is exacerbated…

Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of…

An explicit rate indication scheme for congestion avoidance in computer and telecommunication networks is proposed. The sources monitor their load and provide the information periodically to the switches. The switches, in turn, compute the…

Traditionally, data selection has been studied in settings where all samples from prospective sources are fully revealed to a machine learning developer. However, in practical data exchange scenarios, data providers often reveal only a…

The paper focuses on improving the spectrum sharing using NSU, FLS and Traffic Pattern Prediction and also made comparison that traffic pattern prediction provides a better way of improving the spectrum utilization and avoids the spectrum…

Transistor-level simulation plays a vital role in validating the physical correctness of integrated circuits. However, such simulations are computationally expensive. This paper proposes three novel reduction methods specifically tailored…

ABR traffic management for point-to-multipoint connections controls the source rate to the minimum rate supported by all the branches of the multicast tree. A number of algorithms have been developed for extending ABR congestion avoidance…

This paper addresses the problem of short-term traffic prediction for signalized traffic operations management. Specifically, we focus on predicting sensor states in high-resolution (second-by-second). This contrasts with traditional…

Emerging artificial intelligence (AI) and machine learning (ML) workloads present new challenges of managing the collective communication used in distributed training across hundreds or even thousands of GPUs. This paper presents STrack, a…

Efficient large-scale inference of transformer-based large language models (LLMs) remains a fundamental systems challenge, frequently requiring multi-GPU parallelism to meet stringent latency and throughput targets. Conventional tensor…

Many algorithms for congestion control, scheduling, network measurement, active queue management, security, and load balancing require custom processing of packets as they traverse the data plane of a network switch. To run at line rate,…