High level data parallel languages such as Vienna Fortran and High Performance Fortran (HPF) have been introduced to allow the programming of massively parallel distributed memory machines at a relatively high level o...
详细信息
High level data parallel languages such as Vienna Fortran and High Performance Fortran (HPF) have been introduced to allow the programming of massively parallel distributed memory machines at a relatively high level of abstraction, based on the single program multiple data (SPMD) paradigm. Their main features include mechanisms for expressing the distribution of data across the processors of a machine. The paper introduces additional language functionality to allow the efficient processing of sparse matrix codes. It introduces methods for the representation and distribution of sparse matrices, which forms a powerful mechanism for storing and manipulating sparse matrices able to be efficiently implemented on massively parallel machines.< >
Large language models (LLM), ChatGPT is making substantial impact across various fields. This study for the first time presents a novel approach to the hybrid disassembly line balancing problem using LLM and reinforce...
详细信息
ISBN:
(数字)9798350358513
ISBN:
(纸本)9798350358520
Large language models (LLM), ChatGPT is making substantial impact across various fields. This study for the first time presents a novel approach to the hybrid disassembly line balancing problem using LLM and reinforcement learning algorithms in remanufacturing contexts. The problem is divided into two sub-stages. LLM is innovatively used to capture a disassembly sequence well in the first stage, while reinforcement learning is utilized to address the problem in the second stage. Upon comparing the performance with and without LLM, the proposed approach significantly reduces the trial-and-error space and achieves faster convergence to achieve the desired solution. Future work of this study is also discussed.
暂无评论