Load balancing (electrical power)
View article: D4a.1 Grid balancing development for hydrogen distribution grids: characteristics and key gaps
D4a.1 Grid balancing development for hydrogen distribution grids: characteristics and key gaps Open
As hydrogen is expected to play a pivotal role in the Dutch energy transition, adequate infrastructure is needed to safely and efficiently connect hydrogen supply, storage, and demand. Alongside plans for the national hydrogen infrastructu…
View article: Neural Expert Orchestration: Dynamic Specialization and Load Balancing for Scalable Mixture-of-Experts
Neural Expert Orchestration: Dynamic Specialization and Load Balancing for Scalable Mixture-of-Experts Open
Mixture-of-Experts (MoE) models offer a compelling paradigm for scaling neural networks, enabling immense model capacities without proportional increases in computational cost during inference. However, their practical deployment is often …
View article: Adaptive Neuro-Orchestration: Deep Reinforcement Learning for Real-time Load Balancing in Distributed AI Systems
Adaptive Neuro-Orchestration: Deep Reinforcement Learning for Real-time Load Balancing in Distributed AI Systems Open
The proliferation of Artificial Intelligence (AI) models, particularly deep neural networks, in real-time applications necessitates robust and efficient distributed inference systems. A critical challenge in such systems is dynamic load ba…
View article: Neural Expert Orchestration: Dynamic Specialization and Load Balancing for Scalable Mixture-of-Experts
Neural Expert Orchestration: Dynamic Specialization and Load Balancing for Scalable Mixture-of-Experts Open
Mixture-of-Experts (MoE) models offer a compelling paradigm for scaling neural networks, enabling immense model capacities without proportional increases in computational cost during inference. However, their practical deployment is often …
View article: AI-Driven Predictive Load Orchestration for Distributed LLM Inference
AI-Driven Predictive Load Orchestration for Distributed LLM Inference Open
This paper presents a novel framework for AI-driven predictive load orchestration specifically tailored for distributed Large Language Model (LLM) inference. As LLMs scale in size and complexity, deploying them across distributed computing…
View article: Energy-Efficient Protocols and Autonomous Data Management in Wireless Sensor Networks for Real-Time Psychology Class Applications
Energy-Efficient Protocols and Autonomous Data Management in Wireless Sensor Networks for Real-Time Psychology Class Applications Open
This paper introduces an energy-efficient communication structure and an independent data management plan for Wireless Sensor Networks (WSNs) in a real-time psychology class setting. Since the contemporary classroom is becoming highly depe…
View article: Adaptive Neuro-Orchestration: Deep Reinforcement Learning for Real-time Load Balancing in Distributed AI Systems
Adaptive Neuro-Orchestration: Deep Reinforcement Learning for Real-time Load Balancing in Distributed AI Systems Open
The proliferation of Artificial Intelligence (AI) models, particularly deep neural networks, in real-time applications necessitates robust and efficient distributed inference systems. A critical challenge in such systems is dynamic load ba…
View article: D4a.1 Grid balancing development for hydrogen distribution grids: characteristics and key gaps
D4a.1 Grid balancing development for hydrogen distribution grids: characteristics and key gaps Open
As hydrogen is expected to play a pivotal role in the Dutch energy transition, adequate infrastructure is needed to safely and efficiently connect hydrogen supply, storage, and demand. Alongside plans for the national hydrogen infrastructu…
View article: AI-Driven Predictive Load Orchestration for Distributed LLM Inference
AI-Driven Predictive Load Orchestration for Distributed LLM Inference Open
This paper presents a novel framework for AI-driven predictive load orchestration specifically tailored for distributed Large Language Model (LLM) inference. As LLMs scale in size and complexity, deploying them across distributed computing…
View article: Adaptive Resource Allocation via Multi-Agent Reinforcement Learning for Dynamic Load Balancing in AI Workloads
Adaptive Resource Allocation via Multi-Agent Reinforcement Learning for Dynamic Load Balancing in AI Workloads Open
This paper explores the application of multi-agent reinforcement learning (MARL) to address the challenge of dynamic load balancing in AI workloads. Modern AI applications often involve complex computational tasks that require efficient re…
View article: Beyond Containers: A Serverless and Adaptive Framework for High-Throughput Model Serving
Beyond Containers: A Serverless and Adaptive Framework for High-Throughput Model Serving Open
This paper introduces a novel framework for high-throughput model serving that moves beyond traditional container-based deployments. We propose a serverless and adaptive architecture that dynamically scales resources based on real-time dem…
View article: Adaptive Resource Allocation via Multi-Agent Reinforcement Learning for Dynamic Load Balancing in AI Workloads
Adaptive Resource Allocation via Multi-Agent Reinforcement Learning for Dynamic Load Balancing in AI Workloads Open
This paper explores the application of multi-agent reinforcement learning (MARL) to address the challenge of dynamic load balancing in AI workloads. Modern AI applications often involve complex computational tasks that require efficient re…
View article: Holistic Load Balancing for Heterogeneous AI Infrastructures: A Graph Neural Network Approach
Holistic Load Balancing for Heterogeneous AI Infrastructures: A Graph Neural Network Approach Open
The proliferation of Artificial Intelligence (AI) workloads, ranging from large-scale model training to real-time inference, presents unprecedented challenges for underlying computational infrastructures. These infrastructures are increasi…
View article: Scalable AI Through Hybrid Parallelism: Balancing Data and Model Distribution for Enhanced Performance
Scalable AI Through Hybrid Parallelism: Balancing Data and Model Distribution for Enhanced Performance Open
This paper investigates the challenges and opportunities in scaling Artificial Intelligence (AI) through hybrid parallelism, specifically focusing on balancing data and model distribution for enhanced performance. As AI models grow in size…
View article: Beyond Containers: A Serverless and Adaptive Framework for High-Throughput Model Serving
Beyond Containers: A Serverless and Adaptive Framework for High-Throughput Model Serving Open
This paper introduces a novel framework for high-throughput model serving that moves beyond traditional container-based deployments. We propose a serverless and adaptive architecture that dynamically scales resources based on real-time dem…
View article: Holistic Load Balancing for Heterogeneous AI Infrastructures: A Graph Neural Network Approach
Holistic Load Balancing for Heterogeneous AI Infrastructures: A Graph Neural Network Approach Open
The proliferation of Artificial Intelligence (AI) workloads, ranging from large-scale model training to real-time inference, presents unprecedented challenges for underlying computational infrastructures. These infrastructures are increasi…
View article: Scalable AI Through Hybrid Parallelism: Balancing Data and Model Distribution for Enhanced Performance
Scalable AI Through Hybrid Parallelism: Balancing Data and Model Distribution for Enhanced Performance Open
This paper investigates the challenges and opportunities in scaling Artificial Intelligence (AI) through hybrid parallelism, specifically focusing on balancing data and model distribution for enhanced performance. As AI models grow in size…
View article: Power Consumption and Network Traffic Telemetry Datasets of Carrier-Grade Network Equipment for Smart Energy-aware Zero-touch Traffic Engineering
Power Consumption and Network Traffic Telemetry Datasets of Carrier-Grade Network Equipment for Smart Energy-aware Zero-touch Traffic Engineering Open
To develop a model that characterizes the energy consumption of network equipment, we conducted a series of experiments in a physical network laboratory at Telefónica Innovación Digital premises. The experiments were carried out on two dif…
View article: Power Consumption and Network Traffic Telemetry Datasets of Carrier-Grade Network Equipment for Smart Energy-aware Zero-touch Traffic Engineering
Power Consumption and Network Traffic Telemetry Datasets of Carrier-Grade Network Equipment for Smart Energy-aware Zero-touch Traffic Engineering Open
To develop a model that characterizes the energy consumption of network equipment, we conducted a series of experiments in a physical network laboratory at Telefónica Innovación Digital premises. The experiments were carried out on two dif…
View article: HIFLD OPEN Control Areas
HIFLD OPEN Control Areas Open
This feature class/shapefile represents electric power control areas. Control Areas, also known as Balancing Authority Areas, are controlled by Balancing Authorities, who are responsible for monitoring and balancing the generation, load, a…
View article: Implementasi Algoritma Round Robin dalam Sistem Multi-agent dan Multi-client untuk Load balancing Dinamis pada Jaringan Lokal
Implementasi Algoritma Round Robin dalam Sistem Multi-agent dan Multi-client untuk Load balancing Dinamis pada Jaringan Lokal Open
Load balancing merupakan mekanisme penting dalam sistem layanan web untuk menjamin pemerataan beban kerja dan menjaga kestabilan performa layanan. Penelitian ini mengimplementasikan algoritma Round Robin dalam arsitektur sistem multi-agent…
View article: jipolanco/VortexPasta.jl: v0.32.4
jipolanco/VortexPasta.jl: v0.32.4 Open
VortexPasta v0.32.4 Diff since v0.32.3 Merged pull requests: Test GPU code using OpenCL (#79) (@jipolanco) Improve load balancing when iterating over filament nodes (#80) (@jipolanco)
View article: Quantum optimisation for supply chain: QUBO formulations and QAOA solutions for facility location and load balancing
Quantum optimisation for supply chain: QUBO formulations and QAOA solutions for facility location and load balancing Open
View article: Improved energy efficient load balanced mobility management RPL protocol for mobile internet of things networks
Improved energy efficient load balanced mobility management RPL protocol for mobile internet of things networks Open
View article: MemFine: Memory-Aware Fine-Grained Scheduling for MoE Training
MemFine: Memory-Aware Fine-Grained Scheduling for MoE Training Open
The training of large-scale Mixture of Experts (MoE) models faces a critical memory bottleneck due to severe load imbalance caused by dynamic token routing. This imbalance leads to memory overflow on GPUs with limited capacity, constrainin…
View article: Hybrid Energy-Efficient Routing Protocol for Extended Network Lifetime in Wireless Body Area Networks
Hybrid Energy-Efficient Routing Protocol for Extended Network Lifetime in Wireless Body Area Networks Open
Wireless Body Area Networks (WBANs) are an emerging technology designed to provide extensive applications in different fields. Healthcare is a particularly interesting field for WBANs. This network plays a vital role in remotely monitoring…
View article: PANA: A Fine-Grained Runtime-Adaptive Load Balancing for Parallel SpMV on multicore CPUs
PANA: A Fine-Grained Runtime-Adaptive Load Balancing for Parallel SpMV on multicore CPUs Open
2800 Sparse Matrix Dataset from SuiteSparse Matrix Collection
View article: Batch Denoising for AIGC Service Provisioning in Wireless Edge Networks
Batch Denoising for AIGC Service Provisioning in Wireless Edge Networks Open
Artificial intelligence-generated content (AIGC) service provisioning in wireless edge networks involves two phases: content generation on edge servers and content transmission to mobile devices. In this paper, we take image generation as …
View article: PANA: A Fine-Grained Runtime-Adaptive Load Balancing for Parallel SpMV on multicore CPUs
PANA: A Fine-Grained Runtime-Adaptive Load Balancing for Parallel SpMV on multicore CPUs Open
2800 Sparse Matrix Dataset from SuiteSparse Matrix Collection
View article: Batch Denoising for AIGC Service Provisioning in Wireless Edge Networks
Batch Denoising for AIGC Service Provisioning in Wireless Edge Networks Open
Artificial intelligence-generated content (AIGC) service provisioning in wireless edge networks involves two phases: content generation on edge servers and content transmission to mobile devices. In this paper, we take image generation as …