相关论文: A Multilevel Approach to Topology-Aware Collective…
Unstructured meshes are characterized by data points irregularly distributed in the Euclidian space. Due to the irregular nature of these data, computing connectivity information between the mesh elements requires much more time and memory…
Grid environments have recently been developed with low stretch and overheads that increase with the logarithm of the number of nodes in the system. Getting and sending data to/from a large numbers of nodes is gaining importance due to an…
In this paper, we study the distributed control of networked cyber-physical systems when a much more energy-efficient distributed communication management strategy is proposed to solve the well-studied consensus problem. In contrast to the…
Distribution grid is the medium and low voltage part of a large power system. Structurally, the majority of distribution networks operate radially, such that energized lines form a collection of trees, i.e. forest, with a substation being…
Enabling coordination between products from different vendors is a key characteristic of the design philosophy behind future wireless communication networks. As an example, different devices may have different implementations, leading to…
Higher-order networks are gaining significant scientific attention due to their ability to encode the many-body interactions present in complex systems. However, higher-order networks have the limitation that they only capture many-body…
Fog computing promises to enable machine learning tasks to scale to large amounts of data by distributing processing across connected devices. Two key challenges to achieving this goal are heterogeneity in devices compute resources and…
We present a simple hierarchical communication scheme for distributed Fast Multipole Methods (FMMs) based on MPI neighborhood collectives and uniform trees. The method targets the common case of extending an existing high-performance…
The efficiency and scalability of MPI collective operations, in particular the broadcast operation, plays an integral part in high performance computing applications. MPICH, as one of the contemporary widely-used MPI software stacks,…
As large language models from diverse providers converge toward comparable benchmark performance, the traditional paradigm of selecting a single best model per task yields diminishing returns. We argue that orchestration topology -- the…
In Application layer multicast (ALM) also called Overlay Multicast, multicast-related functionalities are moved to end-hosts. The key advantages, overlays offers, are flexibility, adaptability and ease of deployment [1]. Application layer…
Fog computing emerged as a crucial platform for the deployment of IoT applications. The complexity of such applications requires methods that handle the resource diversity and network structure of Fog devices while maximizing the service…
We present a decentralized and scalable approach for deployment of a robot swarm. Our approach tackles scenarios in which the swarm must reach multiple spatially distributed targets, and enforce the constraint that the robot network cannot…
The traditional approach to distributed machine learning is to adapt learning algorithms to the network, e.g., reducing updates to curb overhead. Networks based on intelligent edge, instead, make it possible to follow the opposite approach,…
In this paper, we consider multiple cache-enabled clients connected to multiple servers through an intermediate network. We design several topology-aware coding strategies for such networks. Based on topology richness of the intermediate…
Internet of Things has pervaded every area of modern life. From a research and industry standpoint, there has been an increasing demand and desire in recent years to develop Internet of Things networks with distributed structure. Wireless…
Two-phase I/O is a well-known strategy for implementing collective MPI-IO functions. It redistributes I/O requests among the calling processes into a form that minimizes the file access costs. As modern parallel computers continue to grow…
The irreducible complexity of natural phenomena has led Graph Neural Networks to be employed as a standard model to perform representation learning tasks on graph-structured data. While their capacity to capture local and global patterns is…
Large language model (LLM)-based multi-agent systems have shown strong potential for complex reasoning by coordinating specialized agents through structured communication. However, existing topology-evolution methods typically construct or…
In this paper we consider spatial networks that realize a balance between an infrastructure cost (the cost of wire needed to connect the network in space) and communication efficiency, measured by average shortest pathlength. A global…