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January 2025
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Fast, stable, elastic GPU resources with dataset and model management for AI cloud platforms.
通过构建云GPU计算资源，具有高并行、高吞吐、低时延 等特点，性能比传统架构显著提高
容器化学习平台实现快速环境部署及作业指派，有效降低 多应用程序安装、迁移复杂度
支持SLURM和K8S双调度系统，及主流计算框架，灵活的 资源调度策略，使训练过程更加高效、弹性
Sugon’s AI cloud-computing platform solution relies on elastic cloud resources at the bottom and, in the middle, uses XMachine high-performance clusters to form a cloud GPU computing platform. Compute data, logs, and model data are stored uniformly in Sugon ParaStor300 distributed parallel storage. Through Sugon’s containerized enterprise distributed deep-learning platform, it provides dataset management, model management, training, and other services. It helps users with multi-group resource allocation, rapid development-environment setup, and flexible application migration. Based on mainstream deep-learning frameworks, it supports Caffe, TensorFlow, and more, combined with Kubernetes and Docker, providing experiment environments, offline jobs, and online services, connecting the full process from model research and batch training to online prediction, perfectly meeting one-stop deep-learning training and real-time inference, and is currently a high cost-performance overall AI training and inference solution.
Cloud-based GPU computing services with elastic, flexible resource scheduling greatly raise GPU utilization and output powerful computing more efficiently and economically.
A containerized deep-learning platform with one-click environment deployment and simple management greatly simplifies building an enterprise deep-learning platform.
Provide users with cloud-based services that lower the economic and technical cost of entering deep learning, helping users efficiently unlock AI potential for real business.
+86 400-810-0466
international@sugon.com
津公网安备 12011602000521号
+86 400-810-0466
international@sugon.com
津公网安备 12011602000521号
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