Lab Overview
Lab Members
Research Projects
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The High-Performance Machine Learning (HPML) Laboratory focuses on developing fast and resource-efficient machine learning algorithms using high-performance computing techniques. Our research concentrates on two primary areas:

  • High-Performance Machine Learning Systems
  • Efficient Machine Learning Algorithms

Collaborating closely with the HPC platform team at HKUST(GZ), our lab is equipped with state-of-the-art computing resources, enabling us to undertake ambitious research endeavors. Our resources include:

  • 19,152 Intel CPUs
  • 2,560 AMD CPUs
  • 1,728 Kunpeng CPUs
  • 528 Nvidia A800 and H100 GPUs
  • 64 Nvidia A30 GPUs
  • 64 Ascend 910 Pro AI Processors
  • 6,573 TB of HDDs
  • 309 TB of SSDs

These formidable computing assets empower us to tackle complex problems in machine learning with unprecedented scale and efficiency.

Furthermore, our lab is supported by multiple competitive research grants, including funding from prestigious institutions such as the National Natural Science Foundation of China (NSFC) and the China Computer Federation (CCF). These grants not only validate the importance of our research but also provide the financial backing necessary to drive innovation and make significant contributions to the field of machine learning.

Through our interdisciplinary approach and dedication to excellence, the HPML Laboratory is poised to continue making breakthroughs that push the boundaries of what is possible in high-performance machine learning.

We have a track record of publications in top-tier conferences and journals. Some recent achievements include:

For more information, please visit the homepages of Prof. Xiaowen CHU, Prof. Qiong LUO  and Prof. Zeyi Wen.

We are actively recruiting talented individuals to join our team. Open positions include opportunities for PhD students, Postdocs, and Research Assistants. If you are passionate about high-performance machine learning and eager to make meaningful contributions to the field, we welcome you to explore opportunities within our dynamic and collaborative research environment.