CoresHub
Coreshub provides GPU cloud services, AI training clusters, parallel file storage, and image repositories, delivering secure, reliable, and high-performance cloud-based AI training and inference environments. The platform offers a range of solutions, including computing power market, model inference, and various industry-specific applications. Coreshub's core team comprises experts from Tsinghua University, leading AI companies, IBM, renowned venture capital firms, and major internet corporations, bringing extensive AI technical expertise and ecosystem resources. The platform emphasizes an independent and open cooperative ecosystem, actively collaborating with AI model suppliers and hardware manufacturers. Coreshub's AI computing platform enables unified scheduling and intelligent management of diverse heterogeneous computing power, meeting AI computing operation, maintenance, and management needs in a one-stop manner.
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Amazon EC2
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers. Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 delivers the broadest choice of compute, networking (up to 400 Gbps), and storage services purpose-built to optimize price performance for ML projects. Build, test, and sign on-demand macOS workloads. Access environments in minutes, dynamically scale capacity as needed, and benefit from AWS’s pay-as-you-go pricing. Access the on-demand infrastructure and capacity you need to run HPC applications faster and cost-effectively. Amazon EC2 delivers secure, reliable, high-performance, and cost-effective compute infrastructure to meet demanding business needs.
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XRCLOUD
GPU cloud computing is a GPU-based computing service with real-time, high-speed parallel computing and floating-point computing capacity. It is ideal for various scenarios such as 3D graphics applications, video decoding, deep learning, and scientific computing. GPU instances can be managed just like a standard ECS with speed and ease, which effectively relieves computing pressures. RTX6000 GPU contains thousands of computing units and shows substantial advantages in parallel computing. For optimized deep learning, massive computing can be completed in a short time. GPU Direct seamlessly supports the transmission of big data among networks. Built-in acceleration framework, it can focus on the core tasks by quick deployment and fast instance distribution. We offer optimal cloud performance at a transparent price. The price of our cloud solution is open and cost-effective. You may choose to charge on-demand, and you can also get more discounts by subscribing to resources.
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Elastic GPU Service
Elastic computing instances with GPU computing accelerators suitable for scenarios (such as artificial intelligence (specifically deep learning and machine learning), high-performance computing, and professional graphics processing).
Elastic GPU Service provides a complete service system that combines software and hardware to help you flexibly allocate resources, elastically scale your system, improve computing power, and lower the cost of your AI-related business. It applies to scenarios (such as deep learning, video encoding and decoding, video processing, scientific computing, graphical visualization, and cloud gaming).
Elastic GPU Service provides GPU-accelerated computing capabilities and ready-to-use, scalable GPU computing resources. GPUs have unique advantages in performing mathematical and geometric computing, especially floating-point and parallel computing. GPUs provide 100 times the computing power of their CPU counterparts.
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