Cover Image

GPU-Accelerated Optimization Solver for Unit Commitment in Large-Scale Power Grids

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sharadga, Hussein, Mohammadi, Javad
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control Hardware Architecture
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hardware-Compatible Single-Shot Feasible-Space Heuristics for Solving the Quadratic Assignment Problem
by: Im, Haesol, et al.
Published: (2025)

Floorplanning with I/O assignment via feasibility-seeking and superiorization methods
by: Yu, Shan, et al.
Published: (2024)

Accelerating Hybrid XOR$-$CNF Boolean Satisfiability Problems Natively with In-Memory Computing
by: Im, Haesol, et al.
Published: (2025)

Parallel Tempering-Inspired Distributed Binary Optimization with In-Memory Computing
by: Zhang, Xiangyi, et al.
Published: (2024)

Optimizing Multi-level Magic State Factories for Fault-Tolerant Quantum Architectures
by: Silva, Allyson, et al.
Published: (2024)

Physics-Constrained Adaptive Neural Networks Enable Real-Time Semiconductor Manufacturing Optimization with Minimal Training Data
by: Guerrero, Rubén Darío
Published: (2025)

Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions
by: Wu, Zhaoxian, et al.
Published: (2025)

In-memory Training on Analog Devices with Limited Conductance States via Multi-tile Residual Learning
by: Li, Jindan, et al.
Published: (2025)

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training
by: Xiao, Quan, et al.
Published: (2026)

Towards Exact Gradient-based Training on Analog In-memory Computing
by: Wu, Zhaoxian, et al.
Published: (2024)

Multi-qubit Lattice Surgery Scheduling
by: Silva, Allyson, et al.
Published: (2024)

On the Convergence Theory of Pipeline Gradient-based Analog In-memory Training
by: Wu, Zhaoxian, et al.
Published: (2024)

A Flexible Precision Scaling Deep Neural Network Accelerator with Efficient Weight Combination
by: Zhao, Liang, et al.
Published: (2025)

EasyRider: Mitigating Power Transients in Datacenter-Scale Training Workloads
by: Jensen, Dillon, et al.
Published: (2026)

Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node
by: Latif, Imran, et al.
Published: (2024)

Switching Frequency as FPGA Monitor: Studying Degradation and Ageing Prognosis at Large Scale
by: Lanzieri, Leandro, et al.
Published: (2024)

GPU-Accelerated Simulated Oscillator Ising/Potts Machine Solving Combinatorial Optimization Problems
by: Gonul, Yilmaz Ege, et al.
Published: (2025)

The Unseen AI Disruptions for Power Grids: LLM-Induced Transients
by: Li, Yuzhuo, et al.
Published: (2024)

FAV-NSS: An HIL Framework for Accelerating Validation of Automotive Network Security Strategies
by: Li, Changhong, et al.
Published: (2025)

Low-Power Encoding for PAM-3 DRAM Bus
by: Nam, Jonghyeon, et al.
Published: (2024)

Heterogeneous Memory Design Exploration for AI Accelerators with a Gain Cell Memory Compiler
by: Wang, Xinxin, et al.
Published: (2026)

RoboGPU: Accelerating GPU Collision Detection for Robotics
by: Liu, Lufei, et al.
Published: (2026)

Large-Scale Network Utility Maximization via GPU-Accelerated Proximal Message Passing
by: Sreekumar, Akshay, et al.
Published: (2025)

GSIM: Accelerating RTL Simulation for Large-Scale Designs
by: Chen, Lu, et al.
Published: (2025)

GAP-LA: GPU-Accelerated Performance-Driven Layer Assignment
by: Zhao, Chunyuan, et al.
Published: (2025)

DEFA: Efficient Deformable Attention Acceleration via Pruning-Assisted Grid-Sampling and Multi-Scale Parallel Processing
by: Xu, Yansong, et al.
Published: (2024)

Multi-Objective Memory Bandwidth Regulation and Cache Partitioning for Multicore Real-Time Systems
by: Sun, Binqi, et al.
Published: (2025)

Towards Intelligent Traffic Signaling in Dhaka City Based on Vehicle Detection and Congestion Optimization
by: Azam, Kazi Ababil, et al.
Published: (2025)

A Low-Power Sparse Deep Learning Accelerator with Optimized Data Reuse
by: Hsu, Kai-Chieh, et al.
Published: (2025)

e-GPU: An Open-Source and Configurable RISC-V Graphic Processing Unit for TinyAI Applications
by: Machetti, Simone, et al.
Published: (2025)

MTU: The Multifunction Tree Unit for Accelerating Zero-Knowledge Proofs
by: Mo, Jianqiao, et al.
Published: (2025)

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems
by: Gundawar, Ayush, et al.
Published: (2024)

Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems
by: Huang, Wei-Hsing, et al.
Published: (2025)

The Magnificent Seven Challenges and Opportunities in Domain-Specific Accelerator Design for Autonomous Systems
by: Neuman, Sabrina M., et al.
Published: (2024)

An Evaluation and Comparison of GPU Hardware and Solver Libraries for Accelerating the OPM Flow Reservoir Simulator
by: Qiu, Tong Dong, et al.
Published: (2023)

Instruction-Based Coordination of Heterogeneous Processing Units for Acceleration of DNN Inference
by: Petropoulos, Anastasios, et al.
Published: (2025)

Edge GPU Aware Multiple AI Model Pipeline for Accelerated MRI Reconstruction and Analysis
by: Majeed, Ashiyana Abdul, et al.
Published: (2025)

ReGate: Enabling Power Gating in Neural Processing Units
by: Xue, Yuqi, et al.
Published: (2025)

EnergAIzer: Fast and Accurate GPU Power Estimation Framework for AI Workloads
by: Lee, Kyungmi, et al.
Published: (2026)

SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators
by: Umuroglu, Yaman, et al.
Published: (2025)