> For the complete documentation index, see [llms.txt](https://docs.janction.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.janction.ai/welcome.md). # Welcome Janction is the first Layer2 to provide verifiable, synergic and scalable AI service. Janction uses smart contracts to automate and dynamize machine learning and artificial intelligence. Key elements like AI models, GPU computing power, data feeding, and data labeling all are integrated into Janction for coprocessing. #### We aim to build a global distributed computing power market, where Janction GPU Marketplace aims to provide unlimited GPU capacity to users at lower costs by aggregating GPUs from multiple sources. Janction will focus on the core design of the Janction cluster GPU pool and its billing system. First, let's analyze the Janction cluster GPU pool and its billing system. The cluster GPU pool is a system for managing and allocating multiple GPU resources, supporting large-scale parallel computing applications. It needs to consider resource scheduling and management, task scheduling, parallel computing, load balancing, resource security and isolation, fault recovery and fault tolerance, cost management and efficiency optimization, proof of work, and consistency issues, among others. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.janction.ai/welcome.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.