IEEE

Dynamic Heuristic Optimization in High-Order Runge–Kutta Schemes Using Reinforcement Learning and Genetic Algorithms

Abstract: This paper introduces a hybrid optimisation framework that integrates Genetic Algorithms (GAs) and Reinforcement Learning (RL) for the construction of high-order Runge–Kutta (RK) schemes.
Semiconductor Engineering

Critical Optimization Factors For GenAI Chipmakers

Some chipmakers aim to outgun the competition with sheer performance. Flagship GPUs, for example, focus on FLOPS and huge ...
IEEE

Reinforcement Guided Genetic Algorithm for Application Mapping in Network-on-Chip Architectures: Towards Transparent and Efficient MPSoC Scheduling

Abstract: In this paper, we present a novel hybrid application mapping framework that integrates Genetic Algorithm (GA) with Reinforcement Learning (RL) to optimize task allocation in 2D ...