Vision

GPGPU: Enterprise-Scale Decentralized GPU Cloud Service

GPGPU is an enterprise-scale decentralized GPU cloud service where anyone can connect and lease their GPU devices for rewards. Compared to traditional centralized cloud services, it offers more efficient and cost-effective solutions while delivering high-quality services. With the rapid development and market expansion of the AI industry, the demand for GPU resources is skyrocketing. However, the supply of GPU resources is insufficient to meet this demand, leading to cost imbalances.

The AI industry market is expected to continue growing at an astonishing rate, bringing innovative changes to many sectors. Despite not yet reaching explosive growth, the supply of GPUs is highly unstable and demands high costs. As the AI industry progresses, the scarcity of GPU power will increase, becoming essential across various industries. Innovative technologies tend to follow a J-curve pattern, leading to an explosion in demand over time. Just as crude oil became a vital industrial driver after the Second Industrial Revolution, bringing immense wealth to Middle Eastern countries, the AI industry is also expected to significantly advance, powered by GPU resources.

Currently, centralized cloud services like Amazon's AWS and Microsoft's Azure can only meet about one-third of the AI and machine learning development demand, exacerbating cost imbalances. GPGPU aims to address this issue by building a global network of idle GPU resources to balance supply and demand, promoting healthy and fair growth in the AI industry.

• Cost: Enterprise-level GPU resources require substantial costs. Cloud-based GPU resources allow for usage without large-scale infrastructure investments and optimize costs by charging only for usage. GPGPU offers GPU resources at more than 1/5th the cost of existing services.

• Scalability and Flexibility: Decentralized GPU cloud services provide the flexibility to scale GPU resources up or down as needed. This ensures quick adaptation to fluctuating resource needs for AI model training or inference.

• Locality: Decentralized GPU cloud services utilize geographically distributed data centers to meet regional demands. This offers advantages in complying with regional regulations and meeting data speed and stability requirements.

• Security: Blockchain technology enhances data integrity and security. Decentralized blockchain-based systems are more resistant to attacks than centralized systems, preventing data tampering or forgery.

• Transparency and Traceability: Blockchain offers transparency and traceability of transactions. When GPU computing resource usage and management are recorded on the blockchain, users can transparently verify resource usage, fostering trust and transparency.

• Decentralized Computing: Blockchain and decentralized GPU cloud services provide computing resources from a decentralized network rather than a centralized system, preventing single points of failure and enhancing system stability.

• Convenience: Building a system with physical devices requires network experts for configuration, as well as security equipment and specialized personnel, incurring complex costs. GPGPU eliminates these procedures, allowing anyone to use GPU resources with simple operations.

Conclusion

The AI industry is continually advancing, increasing the demand for GPU computing resources. The growth rate of the AI industry varies but generally shows positive growth. The development and practical application of deep learning and machine learning algorithms drive this growth. The demand for GPU computing resources is closely linked to AI industry growth, as GPUs are suitable for AI and machine learning tasks due to their ability to handle large-scale data and perform rapid parallel processing. Consequently, GPUs are the primary platform for training and inference of AI models.

Market research reports indicate that the AI industry is growing at an annual rate of approximately 20% to 30%, driven by advancements in AI technology and increased demand for AI-based products and services. The demand for GPU computing resources increases proportionally with AI industry growth. High-performance GPUs are needed for various AI tasks such as large-scale model training, real-time inference, natural language processing, and computer vision. Therefore, GPU manufacturers and cloud service providers are continuously expanding GPU computing resources to meet this demand.

Exact figures can fluctuate annually, and detailed data can be found in specific market research and forecast reports. However, the demand for GPU computing resources is generally expected to grow alongside the AI industry. Decentralized GPU cloud services and blockchain technology offer significant advantages in supplying and managing the GPU computing resources needed for the AI industry. These benefits are critical for efficiently utilizing and managing GPU computing resources in the AI industry, potentially bringing innovative changes to the field.