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Elice Cloud: Advanced GPU Cloud Services for AI Research

Elice

02/01/2023

Inconvenience of Overseas GPU Cloud Services


In the GPU cloud services market, overseas companies still dominate, with Colab being a notable example. Colab offers a free GPU cloud service that allows you to use a Jupyter Notebook environment directly in your browser. In addition to this, there are also companies like Microsoft Azure, Amazon Web Service (AWS), and Google Cloud Platform (GCP) that provide GPU Virtual Machine (VM) services.

However, these overseas services often present challenges for domestic users, including limitations on short-term GPU resource allocation and complex server setups. Moreover, the user guides are sometimes awkwardly translated, making them difficult to use. Additionally, due to domestic laws such as data protection regulations, there are restrictions on the data necessary for AI learning.

To address these issues, domestic IT companies such as KT, Naver, and Kakao have been pioneering the development of GPU cloud services tailored to domestic regulations. Recently, these companies have been working on alleviating the discomfort of local users by developing their own GPU cloud services that comply with domestic laws, pioneering the domestic GPU cloud market. Here, we plan to introduce Elice’s cloud-based GPU services among domestic companies.


Elice Cloud Infrastructure: Elice Cloud


Elice Cloud is built on a modular data center-based GPU server farm infrastructure, designed directly by Elice. It offers customized cloud infrastructure optimized for various DX/DT scenarios at reasonable prices, complying with domestic security regulations. Utilizing top-of-the-line NVIDIA A100 80GB GPUs, Elice Cloud ensures efficient GPU environments through its proprietary dynamic GPU resource allocation and distribution technology.

How can you take advantage of the above features when using Elice Cloud, optimized for domestic environments? One of the services offered by Elice using its GPU cloud infrastructure is Elice Project.


GPU 클라우드, 클라우드 서비스, 주피터 노트북, 프로그래밍 프로젝트, 클라우드 인프라


Elice GPU Cloud Service Project


Elice Project is a service based on GPU-inclusive computing resources and Jupyter Notebook. It is used for AI learning, research, and tasks in programming projects. Elice Project allocates resources such as CPU, RAM, DISK, and GPU to create environments suitable for deep learning and machine learning-based learning, research, and tasks. It provides a Jupyter Notebook-based programming execution environment, allowing users to write and execute code. Elice Project supports one development environment per programming project. Users can code and run their programs using Jupyter Notebook, a tool commonly used by AI researchers. Elice Project is planned to expand its resources to include Visual Studio Code and Orange 3 in the future, providing even more useful features.

*Jupyter Notebook is an integrated development environment where code can be written and executed in various programming languages, including Python. It is an open-source web platform.

For AI researchers and developers, high-performance computer resources like GPUs are essential. Furthermore, there is a growing need for improving collaborative programming project environments among team members. Considering the requirement to handle sensitive data legally, the necessity for domestic data centers has also increased. To address these needs in the GPU cloud services market, Elice launched the Elice Project. The versatility of GPU usage is vast. Let’s explore how Elice Project leverages GPU features.

GPU 클라우드, 클라우드 서비스, 주피터 노트북, 프로그래밍 프로젝트, 클라우드 인프라


Utilizing GPU for Coding Competitions


Coding competitions are events where participants solve real-life problems like stock predictions using methods like machine learning and artificial intelligence. These competitions assess participants’ coding skills and are competitive educational programs. To ensure fair competition, all participants need to work within the same environment, which includes guaranteed runtime, server performance, and time constraints. Only when all conditions are the same can a truly equitable competition be hosted.

Elice Cloud can provide a pre-determined, consistent environment to all participants in coding competitions. It is optimized to maintain consistent performance even when a large number of participants use resources simultaneously. Elice Cloud pricing is based on usage, allowing customizable environment configurations. Recently, Elice Cloud successfully provided resource allocation for a machine learning coding competition with 1,700 participants organized by Company A, ensuring guaranteed performance.

GPU 클라우드, 클라우드 서비스, 주피터 노트북, 프로그래밍 프로젝트, 클라우드 인프라


GPU-Based Lab Exercises with Elice Runbox


Elice Runbox is an integrated education content and learning system based on flexible resource allocation. When conducting in-depth lessons or research in AI, high-performance GPUs are essential. However, high-performance GPUs are often expensive, and the GPU infrastructure can be inadequate. For instance, AI research labs in schools or research institutions usually receive limited GPU resources, imposing constraints on usage.

Elice Runbox aims to resolve issues related to insufficient GPU resources by providing an easy-to-use environment. It supports collaborative participation, making it useful for team projects. Users do not need to manage servers separately, making it incredibly convenient. Furthermore, it can be used with ease without requiring additional installations or updates, enabling convenient utilization of key functions such as code editing and additions. Elice Runbox is designed to allow artificial intelligence exercises to be run on devices such as laptops, mobile phones, and tablets that do not have high-performance GPUs. It installs various services on the computer, enabling AI practice in environments without dedicated powerful GPUs. Elice Runbox is designed to let students conduct AI exercises on cloud-based services without additional costs, even if their hardware resources are limited.

These features showcase how Elice Cloud services can be utilized, addressing the challenges faced by users in existing overseas GPU cloud services. If you’ve experienced inconveniences with overseas GPU cloud services, consider trying Elice Cloud, optimized for the domestic situation. Elice Cloud can address limitations in GPU resource allocation and enable the legal use of sensitive data. Experience the innovation of domestic cloud services with Elice Cloud now!


For those interested in learning more about Elice Cloud services in South Korea - watch now

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*This content is a work protected by copyright law and is copyrighted by Elice.

*The content is prohibited from secondary processing and commercial use without prior consent.

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