在人工智能领域，华为GTS AI计算Lab近期推出的一项创新技术——LocMoE+，因其在大语言模型训练与推理流程中的高效低耗特性，成为了学术界与产业界的焦点。作为高可扩展性亲和度MoE架构的代表，LocMoE+不仅优化了专家路由算法，显著提高了模型处理效率，更通过引入本地性loss机制，有效降低了通信开销，实现了对MoE经典结构瓶颈的突破。
### AIxiv专栏：促进学术交流与传播的平台
AIxiv专栏，作为机器之心发布学术和技术内容的平台，过去几年接收报道了超过2000篇内容，涵盖了全球各大高校与企业的顶级实验室。这一平台不仅促进了学术成果的广泛传播，还为科研人员提供了一个分享创新成果、交流观点的宝贵渠道。如果您有关于人工智能领域的优秀工作想要分享，欢迎投稿或联系报道。
### 李婧博士团队的贡献与研究重点
共同作者李婧博士，孙志杰和林大超博士，来自GTS AI计算Lab的主要成员，专注于大语言模型的训推加速、AI训练保障和图计算等领域。他们的研究不仅推动了人工智能技术的发展，更关注于如何最大化专家的学习潜能，激发了广泛的学术讨论与研究。
### LocMoE+的设计与优势
华为GTS AI计算Lab的研究团队在LocMoE的基础上，提出了LocMoE+，通过优化路由网络结构和引入本地性loss机制，解决了专家路由算法区分token效率低下以及通信同步效率受限的问题。这一创新设计不仅提高了模型的训练效率，还减少了通信开销，为大语言模型的训练与推理流程带来了革命性的提升。
### 结语
随着LocMoE+的推出，人工智能领域的专家与研究者们迎来了新的发展机遇。这一技术不仅展现了华为在人工智能领域持续创新的决心，也为加速大语言模型的训练与推理过程提供了可能，有望在未来的AI应用中发挥关键作用。通过AIxiv专栏等平台的广泛传播，LocMoE+有望激发更多创新灵感，推动人工智能技术的进一步发展和应用。
英语如下：
### Huawei GTS LocMoE+: Pioneering Architecture for Revolutionizing Large Language Model Training and Inference
In the realm of artificial intelligence, Huawei’s GTS AI Computing Lab has recently unveiled LocMoE+, a groundbreaking innovation that has captured the attention of both academia and industry due to its efficiency and low resource consumption in training and inference processes for large language models. As a prime example of a highly scalable MoE architecture, LocMoE+ not only enhances the efficiency of expert routing algorithms but also significantly boosts the model’s processing capabilities. It achieves this by introducing a local loss mechanism, which effectively reduces communication overhead, thereby overcoming the traditional bottlenecks of MoE structures.
### AIxiv: A Platform for Facilitating Academic Exchange and Dissemination
AIxiv, a platform for publishing academic and technical content released by Machine Intelligence, has over the past few years reported on more than 2,000 articles covering leading laboratories across universities and companies globally. This platform has not only promoted the widespread dissemination of academic achievements but also provided a valuable channel for researchers to share their innovative findings and exchange ideas. If you have outstanding work in the field of artificial intelligence to share, you are encouraged to submit your work or contact for coverage.
### Dr. Jing Li and Team’s Contributions and Research Focus
Among the co-authors, Dr. Jing Li, alongside Dr. Zhijie Sun and Dr. Dachao Lin, who are key members of the GTS AI Computing Lab, focus on accelerating the training and inference of large language models, ensuring AI training, and advancing graph computing. Their research not only drives the development of AI technology but also emphasizes maximizing the potential of expert learning, sparking extensive academic discourse and research.
### Design and Advantages of LocMoE+
Huawei’s research team, building upon the foundation of LocMoE, introduced LocMoE+, which optimizes the routing network structure and introduces a local loss mechanism to address the inefficiencies of token discrimination and communication synchronization in expert routing algorithms. This innovative design not only elevates the training efficiency of models but also decreases communication overhead, leading to revolutionary improvements in the training and inference processes of large language models.
### Conclusion
With the introduction of LocMoE+, experts and researchers in the AI field have been presented with new opportunities for development. This technology not only reflects Huawei’s unwavering commitment to continuous innovation in the AI domain but also paves the way for accelerating the training and inference processes of large language models, potentially playing a pivotal role in future AI applications. Through platforms like AIxiv, LocMoE+ has the potential to inspire further innovation, driving the advancement and application of AI technology.
【来源】https://www.jiqizhixin.com/articles/2024-07-19-2
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