August 07, 2026
Northwest University of Political Science and Law: Unified computing power supports the integration of AIGC and digital media in teaching.
Unified GPU computing infrastructure for AIGC education and digital media teaching, enabling flexible resource sharing across AI, graphics, and creative workloads.
| 3 AI Servers | 18× NVIDIA A6000 GPUs | Unified AIPaaS |
Project Overview
The School of Journalism and Communication at Northwest University of Political Science and Law aims to integrate general AI education with Digital Media Art programs. To achieve this, the university adopted OE Cloud’s unified computing infrastructure, consolidating digital media course environments and the AIGC teaching platform into a shared computing resource pool.
Through flexible GPU resource allocation and time-sharing, the platform supports graphics design, video production, creative coding, and AIGC experiments within the same infrastructure, enabling efficient integration of professional education with AI-powered teaching.
User Requirements
| 3D & VIDEO 3D Design and Video Editing Cinema 4D, Adobe Premiere Pro, and CapCut for 3D design, video production, and professional media editing courses. | DESIGN & ANIMATION Graphic Design and Motion Graphics Adobe Photoshop, Illustrator, and After Effects for graphic design, visual creation, and motion graphics production. | |
| CREATIVE TECHNOLOGY Creative Coding and Interactive Art Processing and TouchDesigner support creative programming, interactive media, and digital art teaching. | AI EDUCATION General AI Education Misui AIGC Platform and large-model experimentation environments provide practical support for general AI education and AIGC-based teaching. | |
Solution
| 01 High-Performance GPU Infrastructure Deployed 3 AI servers, each equipped with dual Intel Xeon 8380 processors, 1024 GB memory, and 6 NVIDIA A6000 GPUs. | 02 Unified AIPaaS Computing Infrastructure Built a unified AIPaaS computing infrastructure to host both the AIGC teaching platform (Misui + DeepSeek) and cloud desktop teaching environments. | |
| 03 Flexible GPU Memory Profiles Supports flexible switching between 8 GB and 12 GB GPU memory profiles to meet the requirements of different courses, applications, and teaching environments. | 04 AI and Graphics Workload Integration Integrates AIGC models, graphics workloads, and computer lab environments into a unified platform for centralized computing resource management. | |
| 05 Shared GPU Resource Pool Text-to-image generation, AI experiments, video editing, and digital media courses share the same GPU resource pool through time-based resource reuse. | ||
Customer Value
| Unified Computing Resource Pool A single infrastructure supports both AIGC applications and digital media teaching, reducing duplicated hardware investment. | Flexible GPU Scheduling GPU resources can be dynamically allocated between AI workloads and graphics-intensive teaching applications. | On-Demand GPU Memory Different GPU memory profiles can be quickly switched to support diverse teaching environments and application requirements. | ||
| AI-Integrated Professional Education Supports both conventional digital media courses and innovative “AI + Education” scenarios on the same platform. | Improved Resource Utilization Multiple teaching workloads share the same computing infrastructure, maximizing GPU utilization and overall infrastructure value. |
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