  Large Language Models (LLMs) have recently shown remarkable capabilities in
various software engineering tasks, spurring the rapid development of the Large
Language Models for Software Engineering (LLM4SE) area. However, limited
attention has been paid to crafting efficient LLM4SE solutions that demand
minimal time and memory resources, as well as green LLM4SE solutions that
reduce energy consumption and carbon emissions.
  This 2030 Software Engineering position paper aims to redirect the focus of
the research community towards the efficiency and greenness of LLM4SE, while
also sharing potential research directions to achieve this goal. It commences
with a brief overview of the significance of LLM4SE and highlights the need for
efficient and green LLM4SE solutions. Subsequently, the paper presents a vision
for a future where efficient and green LLM4SE revolutionizes the software
engineering tool landscape, benefiting various stakeholders, including
industry, individual practitioners, and society. The paper then delineates a
roadmap for future research, outlining specific research paths and potential
solutions for the research community to pursue. While not intended to be a
definitive guide, the paper aims to inspire further progress, with the ultimate
goal of establishing efficient and green LLM4SE as a central element in the
future of software engineering.
