Laminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completion

Autor:	Zahra, Zaynab, Li, Zihao, Filgueira, Rosa
Rok vydání:	2023
Předmět:	Computer Science - Distributed Parallel and Cluster Computing Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This paper introduces Laminar, a novel serverless framework based on dispel4py, a parallel stream-based dataflow library. Laminar efficiently manages streaming workflows and components through a dedicated registry, offering a seamless serverless experience. Leveraging large lenguage models, Laminar enhances the framework with semantic code search, code summarization, and code completion. This contribution enhances serverless computing by simplifying the execution of streaming computations, managing data streams more efficiently, and offering a valuable tool for both researchers and practitioners. Comment: 13 pages, 10 Figures, 6 Tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2309.00584 Zobrazit plný text záznamu View this record from Arxiv