# ABSTRACT Graphic Processing Units have been playing a vital role in the development of the current technological sector. Industries & businesses today increasingly depend on these virtual machines to meet the soaring demands of artificial intelligence, data analytics, cryptocurrency mining, generative AI and other high-performance computing applications. Due to the rapid surge in the consumption of GPUs worldwide there has been a severe shortage in the production and availability of these coveted devices. Although there are numerous cloud facilities available, they are quite expensive to avail on demand. GPU.Net aims to address these challenges by building a decentralized platform that connects GPU providers to GPU consumers. GPU providers can attach their machine to the GPU.Net platform and earn GPU tokens for their idle time or total compute contribution. GPU consumers can access the vast infrastructure of GPU.Net by paying in tokens while ensuring scalability, affordability and security of their data and models. Our unique security models are best in class towards building fool proof systems, GPU.Net will pilot Fully Homomorphic Encryption (FHE) technology to ensure complete data privacy, in combination with the platform’s decentralization, preventing them from being accessed by any third parties while promoting a robust and resilient ecosystem. This whitepaper highlights GPU.Net, its developments and the core fundamentals that would play a primary role in the revolution of GPUs and its utilization. --- # Agent Instructions: 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: ``` GET https://gpu-network.gitbook.io/gpu-network-whitepaper/abstract.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.