I. INFORMATION

Hi-Tech Cloud GPU is a service providing virtual servers integrated with NVIDIA graphics cards (GPUs) to serve organizations and businesses in research, development and deployment of Artificial Intelligence (AI) systems and software applications in labs and production, high-quality image and video rendering software, 3D architectural graphics, video transcoding.

The hTGPU service infrastructure is built and operated at Rated 3 - ANSI/TIA942-B data centers and many other international standard certifications such as ISO 9001:2015, ISO 27001:2013, ISO 20001:2018, ISO 27017:2015.

II. FEATURES

1. Virtual Server Connection: Initialize multiple Cloud GPU virtual servers connected together to divide workload, increase processing performance for tasks such as Distributed Training.
2. Compatibility: Connect Hi-Tech Cloud GPU and computing services (Hi-Tech Cloud Server, Hi-Tech Virtual Private Cloud), storage (Hi-Tech File Storage) and backup (Hi-Tech Cloud Backup) to best serve usage needs through a secure, safe connection.
3. Load Balancer & Firewall: Optionally purchase add-on components Loadbalancer, Firewall at reasonable cost to ensure performance & system protection, data security.

III. BENEFITS

1. Accelerate processing, save time: NVIDIA GPUs help accelerate AI model training and inference tasks by 10-30 times compared to using only CPU, reducing processing time from Days to Hours, Minutes, Seconds, customers no longer have to wait long.
2. Ready to use, meeting many groups of needs: Cloud GPU virtual servers are pre-installed with operating systems (Windows/Ubuntu/CentOS), NVIDIA Driver and CUDA Toolkit. The service fully supports popular Machine Learning frameworks and applications (TensorFlow, Caffe, PyTorch), meeting 3D graphics needs (3DS Max, Maya), video transcoding (Adobe Media Encoder, Handbrake).
3. Quick initialization, flexible upgrade: Inheriting the advantages of the Public Cloud platform, Hi-Tech Cloud GPU service can initialize & upgrade resources flexibly whenever customers need, without having to wait as long as when deploying physical infrastructure themselves.

IV. USE CASES

1. Deep Learning Training & Inference: Enterprises, organizations, and universities that need to research, develop, operate, and provide systems and software for Face ID, eKYC, AI Voice Assistant, AI Camera, and OCR.
2. Video Transcoding: Enterprises and organizations that provide live streaming services, movie and video viewing platforms, and television stations in provinces and cities.
3. 3D Visualization - Rendering: Enterprises, design studios, architects, and game studios that need to model objects and 3D design drawings.