Market entry strategy

GPU Providers

Corporations and Institutions

The core appeal for corporations and institutions is cost reduction. Owning a GPU server center involves high initial costs, as well as ongoing expenses for infrastructure, security, and maintenance. While these organizations can offset these costs through their revenue models, GPGPU offers an opportunity to generate additional income and reduce server center expenses.

Typically, GPU server centers owned by corporations and institutions operate at less than 50% utilization throughout the year, leaving significant periods of inactivity. By providing GPU resources through GPGPU and generating additional income, these organizations can recover the cost of their GPU infrastructure within five years, even under conservative estimates.

Monthly Rental Income = (Hourly Rental Rate after Discount) × (Rental Hours per Day) × (30 Days)

Payback Period (Months) = (Equipment Price) / (Hourly Rental Rate × (1 - Discount Rate) × 24 × 30)

First, target corporations with technical capabilities and resources suitable for collaboration with GPGPU. Finding partners that can synergize with the decentralized GPU cloud service is crucial. Distribute proposals that clearly convey the value of the services GPGPU can provide. Companies with GPU server centers primarily use them for their operations but do not fully utilize these resources. Thus, integrating idle resources into GPGPU can create additional revenue streams and expand business models.

Once collaboration begins, promptly address technical and operational issues and use the data collected to enhance the collaboration model. Joint marketing and branding activities can help promote the market. Collaborative marketing allows companies to leverage their networks to reach a broader audience of potential customers. This process can also help lower initial market entry barriers by identifying and securing new collaboration partners. By leveraging the synergies of each other's services, new differentiated services or solutions can be developed to establish a market differentiation strategy.

In conclusion, we will list and select corporations with GPU server centers and secure GPU resources through collaborative agreements. Successful market entry requires sequential approaches: market research, clear value propositions, test programs, joint marketing, and continuous performance measurement and improvement. This strategy maximizes collaboration synergy and solidifies market presence.

Additionally, corporations and institutions that provide GPU resources often operate businesses that require AI or GPU resources. Therefore, they can register their big data, processed data, and AI modules in the GPGPU AI market to create a third revenue stream. This opportunity not only generates revenue from providing GPUs but also expands their business models.

Crypto De-Pin Companies

De-Pin (Decentralized Physical Infrastructure Networks) decentralizes and manages physical infrastructure using blockchain technology. Unlike traditional centralized infrastructure operations, participants collaboratively build and operate infrastructure through decentralized networks.

GPGPU, as a De-Pin, can synergize with various De-Pin and AI financial projects in the cryptocurrency market. These projects have their communities, ranging from tens of thousands to hundreds of thousands of participants. Collaboration can help share and expand these communities.

• Render Network: A decentralized GPU computing network that enables users to utilize spare GPU resources for complex 3D rendering tasks. This service provides cost-effective and fast rendering, allowing artists and designers to focus on creative work.

• IoTeX: Connects IoT devices to a blockchain network, enhancing data security and privacy. IoTeX offers decentralized identity authentication and data management solutions, promoting interoperability among devices. Participants are rewarded with IOTX tokens, ensuring data reliability.

• Filecoin: A decentralized data storage network that allows users to provide spare storage space and use file storage and retrieval services. This reduces dependence on centralized servers and enhances data security and integrity.

• Akash Network: A decentralized cloud computing platform that enables users to rent spare computing resources for cloud services. This reduces cloud service costs and offers a more secure and flexible computing environment through decentralization.

• Bittensor: A decentralized AI network where participants share and collaborate on machine learning models to improve AI performance. This promotes decentralized AI research and development while ensuring data security.

Decentralized GPU networks like Render Network can share GPU resources to maintain a stable supply level. Additionally, decentralized storage services like Filecoin can provide the necessary storage space for GPGPU users. De-Pin projects are generally open to collaboration and are willing to take bold steps to expand their services. GPGPU has identified 50 potential collaborators and plans to propose collaborations starting in Q3 2024, focusing on GPU resource provision and technical support.

Individuals

Individuals are primarily attracted by the potential value increase of tokens. Targeting those with experience in purchasing and operating Node licenses in the cryptocurrency market or with basic investment knowledge, GPGPU has secured KOL (crypto influencer) marketing channels for content distribution (influencer list attached).

Specifically, we plan to conduct team-based competitions in the form of virtual mining (web game format) to continuously increase touchpoints with the decentralized GPU cloud market and GPGPU. Pre-launch events for this point system will be an attractive means for individuals seeking early participation and profit opportunities before the service officially launches.

GPU Users

Period-Focused Users

Game developers, movie, and animation studios require large-scale 3D rendering. During production periods, especially smaller companies, cannot afford to build GPU server centers due to high initial costs and ongoing infrastructure maintenance expenses. For these users, GPGPU offers a more affordable and time-efficient alternative to traditional methods.

Non-Commercial Users

Research facilities in medical and scientific fields are non-commercial organizations but require constant GPU resources. These facilities need high-performance computing resources for data analysis, simulations, and modeling, but their budgets are limited, and cost efficiency is paramount.

Decentralized GPU cloud services are a highly suitable solution for these research facilities. They offer GPU resources at a lower cost than traditional centralized cloud services, with the flexibility to scale up or down as needed. Additionally, the decentralized structure provides high security and data integrity, ensuring the safe management of sensitive research data. These factors combine to maximize research efficiency in medical and scientific fields through cost-effective and high-performance decentralized GPU cloud services.

Enterprise-Scale Users

Commercial enterprise-scale services can utilize high-performance GPU resources through GPGPU's industrial GPU pool. Comprising DL/ML-specific devices like NVIDIA's A100 and H100, this industrial pool is optimized for large-scale data processing and complex computations, providing 24/7 reliable service. Decentralized GPU cloud services offer these high-performance infrastructures cost-effectively, enabling flexible resource scaling and high security, allowing users to optimize computing resources as needed.

Token Airdrop

Combining decentralized protocols and token economics can drive explosive initial user participation. GPGPU members (GPU providers and users, Node operators) are rewarded with $GP tokens for their participation. $GP, the native token of GPGPU, is used for payments, reward systems, and governance operations.

By leveraging transaction fees, period contract margins, rental fees, subscription fees, and attractive discounts, GPGPU provides a cost-effective and flexible solution for GPU providers and users, fostering a sustainable and efficient AI and computing ecosystem.