GUP computing power server

GPU accelerated deep learning models can not only uncover hidden patterns from massive amounts of experimental and observational data, but also directly participate in the construction of scientific theories themselves: from predicting billions of fold spaces for proteins to reverse engineering new materials with specific properties; From decoding complex nonlinear interactions in climate systems to accelerating virtual drug screening of compound libraries. This' new engine 'is deeply integrating the inductive ability of artificial intelligence with the deductive logic of principles, accelerating the evolution of scientific research paradigms from traditional' hypothesis experiment 'to an intelligent cycle of' data prediction verification '. Therefore, building an agile, efficient, and easy to collaborate GPU computing platform is not only a tool choice to improve the efficiency of individual projects, but also a strategic infrastructure for universities and laboratories to cultivate interdisciplinary talents, nurture original achievements, and maintain cutting-edge scientific research competitiveness.

1. Artificial Intelligence and Machine Learning

·Deep learning model training: supports the training and inference of computer vision (image recognition, object detection), natural language processing (big language models, machine translation), speech recognition and other models.

·Automated scientific research: used for automated experimental design, data analysis, and scientific discovery, accelerating the scientific research process.

2. Computational Science and Engineering Simulation

·Computational Fluid Dynamics (CFD): Simulating the aerodynamic design of airplanes, cars, or climate change models.

·Finite Element Analysis (FEA): Used for structural stress simulation in the fields of machinery, civil engineering, and aerospace.

·Material simulation: GPU accelerated electronic structure calculations in molecular dynamics (such as LAMMPS) and quantum chemistry calculations (such as VASP).

3. Life Science and Pharmaceutical Research

·Bioinformatics: Genomic sequencing data analysis, protein structure prediction (such as AlphaFold).

·Drug development: Molecular docking simulation, virtual screening, accelerating candidate drug discovery.

·Medical imaging analysis: 3D reconstruction of MRI and CT images and training of disease diagnosis models.

4. Physics and Astronomy Research

·High energy physics: processing massive amounts of data generated from experiments such as the Large Hadron Collider (LHC).

·Astrophysical simulation: N-body simulation of cosmic evolution and galaxy formation.

·Quantum computing simulation: Using classical GPU to simulate quantum bit behavior and assist in quantum algorithm research.

5. Earth Science and Environmental Research

·Climate modeling: high-resolution climate simulation, predicting weather and long-term changes.

·Remote sensing data processing: real-time analysis of satellite images for disaster monitoring and ecological assessment.

6. Interdisciplinary and Emerging Fields

·Digital Humanities: Large scale historical text analysis, social network computing.

·Computational Social Sciences: Agent based Simulation (ABM), Big Data Social Behavior Analysis.

·Robotics: Reinforcement learning training, real-time perception and control.

Focusing on "AI computing power+enterprise level cloud services", providing a cloud platform with "high-performance computing resources+full process service support" for AI model training/inference and industry intelligent application landing, helping enterprises reduce AI deployment costs and improve business efficiency.

AI heterogeneous computing power service

Heterogeneous data management and intelligent scheduling: supports heterogeneous computing power management for multiple brands of GPU cards; Multi strategy scheduling engine reduces resource fragmentation and improves utilization.

Integrated management of general computing, supercomputing, and intelligent computing: supports unified management of general computing, supercomputing, and intelligent computing, simplifying user usage; Breaking the chimney of computing power, smoothly transferring computing power across systems, and maximizing efficiency.

Fine operation and efficient FinOps: flexible metering and billing strategies to meet complex operational needs; Provide FinOps analysis and dynamically optimize strategy implementation costs.

➢ Support one click deployment of DeepSeek: Support DeepSeek inference model, out of the box, reduce the threshold for AI application development, and accelerate the application and development of AI technology.

Massive model management

Provide full lifecycle management capabilities for large models, including data processing, model training, model evaluation, model deployment, and model inference

Built in massive selection of large models and high-quality datasets, supporting multiple fine-tuning training methods

Efficiently adapting to personalized needs, providing users with out of the box, stable and reliable model development services, achieving customization of large models with low barriers to entry, and accelerating the implementation of models in enterprise application scenarios.

Rapid implementation of intelligent agent scenarios

Provide an integrated solution of "computing power+deployment+optimization" for domestic computing power/edge computing power scenarios

➢ Support rapid development of intelligent agent scenarios, greatly simplify the development process, and reduce the professional requirements of development

Accelerate creative conversion through content generation, provide new tools and solutions for enterprises, and promote business model upgrading and innovative exploration

Through data analysis intelligent agents and knowledge retrieval capabilities, integrate enterprise data resources, provide real-time analysis and predictive support, and provide data support for business process optimization and business decision-making