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On June 6, 2024, Binance issued an announcement stating that Binance’s new coin mining has now launched the 55th project IO.NET (IO), a decentralized artificial intelligence computing and cloud platform. 1. Understanding IO.NET (IO) io.net is a distributed GPU system based on Solana, Render, Ray, and Filecoin, designed to leverage distributed GPU resources to solve computing challenges in the fields of AI and machine learning. io.net solves the problem of insufficient computing resources by aggregating underutilized computing resources such as independent data processing centers, cryptocurrency miners, and excess GPUs from crypto projects such as Filecoin and Render, enabling engineers to obtain large amounts of computing power in an easily accessible, customizable, and low-cost system. Additionally, io.net introduces a Distributed Physical Infrastructure Network (DePin), combining resources from a variety of providers to enable engineers to access massive amounts of computing power in a customizable, cost-effective, and easy-to-implement manner. io cloud now has more than 95,000 GPUs and more than 1,000 CPUs, supports fast deployment, choice of hardware, geography, and provides a transparent payment process. Token Economics and Binance Launchpool (1) Token situation Token name: IO.NET (IO) Maximum token supply: 800,000,000 IO Initial circulation: 95,000,000 IO (19% of the total initial token supply)
(2) Launchpool mining situation Mining Pools: BNB Mining Pool: A total of 17,000,000 IO can be mined (accounting for 85%) FDUSD mining pool: a total of 3,000,000 IO can be mined (accounting for 15%) Mining time: 08:00 on June 7, 2024 to 07:59 on June 11, 2024, GMT+8
3. Core Mechanism 3.1 Centralized resource aggregation io.net's decentralized resource aggregation is one of its core features, which enables the platform to utilize decentralized GPU resources around the world to provide the necessary computing support for AI and machine learning tasks. The goal of this resource aggregation strategy is to optimize resource usage, reduce costs, and provide wider accessibility. The following is a detailed description: 3.1.1 Advantages Cost-effectiveness: By leveraging underutilized GPU resources in the market, io.net is able to provide lower-cost computing power than traditional cloud services. This is especially important for data-intensive AI applications, which often require a large amount of computing resources, which can be costly in traditional ways. Scalability and flexibility: The decentralized model allows io.net to easily expand its resource pool without relying on a single vendor or data center. This model provides users with the flexibility to choose the resources that best suit their task requirements.
3.1.2 Working Principle Diversity of resource sources: io.net aggregates GPU resources from multiple sources, including independent data centers, individual cryptocurrency miners, and excess resources participating in other crypto projects such as Filecoin and Render. Technical implementation: The platform uses blockchain technology to track and manage these resources, ensuring transparency and fairness in resource allocation. Blockchain technology also helps automate payments and incentives for users who contribute additional computing power to the network.
3.1.3 Specific steps Resource discovery and registration: Resource providers (such as GPU owners) register their devices with the io.net platform. The platform verifies the performance and reliability of these resources to ensure that they meet specific standards and requirements. Resource pooling: Verified resources are added to the global resource pool and are available for rent by platform users. The distribution and management of resources are automatically executed through smart contracts, ensuring the transparency and efficiency of the processing process. Dynamic resource allocation: When a user initiates a computing task, the platform dynamically allocates resources based on the task requirements (such as computing power, memory, network bandwidth, etc.). Resource allocation takes into account cost efficiency and geographic location, optimizing task execution speed and cost.
3.2 Dual Token Economic System io.net's dual-token economic system is one of the core features of its blockchain network, designed to incentivize network participants and ensure the efficiency and sustainability of the platform's operations. This system includes two tokens: $IO and $IOSD, each of which plays a unique role. The following is a detailed introduction to the structure and function of this economic system. 3.2.1 $IO Token $IO is the main utility token of the io.net platform and is used for a variety of network transactions and operations. Its main uses include: Payments and Fees: Users use $IO to pay for the rental of computing resources, including GPU usage. In addition, $IO is also used to pay for various services and fees on the network. Resource incentives: $IO tokens are issued as rewards to users who provide GPU computing power or participate in maintaining the network, encouraging them to continue contributing resources. Governance: $IO token holders can participate in the governance decisions of the io.net platform, including voting rights, influencing the future development direction and policy adjustments of the platform.
3.2.2 $IOSD Token $IOSD is a stablecoin pegged to the US dollar, designed to provide a stable value storage and transaction medium for the io.net platform. The main functions are as follows: Stable Value: The value of $IOSD is fixed at 1:1 with the US dollar, providing users with a payment method that is protected from crypto market fluctuations. Easy transactions: Users can use $IOSD to pay platform fees, such as computing resource fees, to ensure the stability and predictability of transaction value. Fee Coverage: Certain network operations or transaction fees can be paid in $IOSD, simplifying the fee settlement process.
3.2.3 Working Mechanism of Dual Token System io.net’s dual token system interacts in several ways to support the operation and growth of the network: Resource Provider Incentives: Resource providers (such as GPU owners) receive $IO tokens in return for contributing their devices to the network. These tokens can be used to further purchase computing resources or traded on the market. Fee Payment: Users use $IO or $IOSD to pay for the use of computing resources. Choosing $IOSD can avoid the risks brought by cryptocurrency fluctuations. Economic Activity Incentives: Through the circulation and use of $IO and $IOSD, the io.net platform is able to stimulate economic activity and increase the liquidity and participation of the network. Governance Participation: $IO tokens also act as governance tokens, enabling holders to participate in the platform’s governance process, such as proposing and voting decisions.
3.3 Dynamic resource allocation and scheduling io.net's dynamic resource allocation and scheduling is one of the core functions of the platform. The key lies in efficiently managing and optimizing the use of computing resources to meet the diverse computing needs of users. This system ensures that computing tasks can be executed on the most appropriate resources in an intelligent and automated manner, while maximizing resource utilization and performance. Here are the various aspects of this mechanism in detail: 3.3.1 Dynamic Resource Allocation Mechanism 1. Resource identification and classification: When a resource provider connects its GPU or other computing resources to the io.net platform, the system first identifies and classifies these resources. This includes evaluating their performance indicators such as processing speed, memory capacity, network bandwidth, etc. These resources are then tagged and archived so that they can be dynamically deployed based on the needs of different tasks.
2. Demand matching: When users submit computing tasks to io.net, they need to specify the requirements of the task, such as the required computing power, memory size, budget limits, etc. The platform's scheduling system analyzes these requirements and selects matching resources from the resource pool.
3. Intelligent scheduling algorithm: Advanced algorithms are used to automatically match the most suitable resource to the submitted task. These algorithms take into account the resource's performance, cost efficiency, geographic location (to reduce latency), and the user's specific preferences. The scheduling system also monitors the real-time status of resources, such as availability and load, to dynamically adjust resource allocation.
3.3.2 Scheduling and Execution 1. Task queue and priority management: All tasks are queued according to priority and submission time. The system processes the task queue according to preset or dynamically adjusted priority rules. Urgent or high-priority tasks can receive a quick response, while long-term or cost-sensitive tasks may be performed during low-cost periods.
2. Fault tolerance and load balancing: The dynamic resource allocation system includes a fault-tolerant mechanism to ensure that even when some resources fail, tasks can be smoothly migrated to other healthy resources to continue execution. Load balancing technology ensures that no single resource is overloaded and optimizes the performance of the entire network by properly distributing the task load.
3. Monitoring and Adjustment: The system continuously monitors the execution status of all tasks and the operating status of resources. This includes real-time analysis of key performance indicators such as task progress and resource consumption. Based on this data, the system may automatically readjust resource allocation to optimize task execution efficiency and resource utilization.
3.3.3 User Interaction and Feedback Transparent User Interface: io.net provides an intuitive user interface that allows users to easily submit tasks, view task status, and adjust requirements or priorities. Feedback mechanism: Users can provide feedback on the results of task execution, and the system adjusts the resource allocation strategy for future tasks based on the feedback to better meet user needs.
4. System Architecture 4.1 IO Cloud IO Cloud is designed to simplify the deployment and management of decentralized GPU clusters, providing machine learning engineers and developers with scalable and flexible access to GPU resources without significant hardware investment. This platform provides an experience similar to traditional cloud services, but with the advantages of a decentralized network. Highlights: Scalability and Affordability: Designed to be the most cost-effective GPU cloud, reducing AI/ML project costs by up to 90%. Integration with IO SDK: Enhance AI project performance through seamless integration to create a unified high-performance environment. Global coverage: Distributed GPU resources, optimized machine learning services and inference, similar to CDN. RAY framework support: Scalable Python application development using the RAY distributed computing framework. Exclusive feature: Provides private access to the OpenAI ChatGPT plugin for easy deployment of training clusters. Crypto Mining Innovation: Seeking to revolutionize crypto mining by supporting the machine learning and artificial intelligence ecosystem.
4.2 IO Worker IO Worker aims to simplify and optimize provisioning operations for WebApp users. This includes user account management, real-time activity monitoring, temperature and power consumption tracking, installation support, wallet management, security, and profitability analysis. Highlights: Worker Homepage: Provides a dashboard for real-time monitoring of connected devices, with the ability to delete and rename devices. Device details page: Displays comprehensive device analysis, including traffic, connection status, and work history. Earnings & Rewards Page: Track earnings and work history, transaction details can be accessed on SOLSCAN. Add New Device Page: Simplifies the device connection process, enabling quick and easy integration.
4.3 IO Explorer IO Explorer is designed as a comprehensive platform that provides users with deep insights into the io.net network operations, similar to how blockchain explorers provide transparency into blockchain transactions. Its main goal is to enable users to monitor, analyze and understand the details of the GPU Cloud, ensuring full visibility into network activity, statistics and transactions while protecting the privacy of sensitive information. advantage: Browser Homepage: Provides insights into supply, verified vendors, active hardware counts, and real-time market pricing. Clusters page: Displays public information about clusters deployed in the network, along with real-time metrics and subscription details. Devices page: Displays public details of devices connected to the network, providing real-time data and transaction tracking. Real-time cluster monitoring: Provides instant insight into cluster status, health, and performance, ensuring users have the latest information.
4.4 IO-SDK IO-SDK is the foundational technology of Io.net, derived from a branch of Ray technology. It enables tasks to run in parallel and process different languages, and is compatible with major machine learning (ML) frameworks, making IO.NET flexible and efficient for a variety of computing needs. This setup, coupled with a set of clearly defined technologies, ensures that IO.NET Portal can meet today's needs and adapt to future changes. Application of multi-layer architecture User Interface: Serves as the visual front end for users, including the public website, client area, and GPU provider area. Designed to be intuitive and user-friendly. Security layer: Ensures the integrity and security of the system, including network protection, user authentication, and activity logging. API layer: Serves as a communication hub for websites, providers, and internal management, facilitating data exchange and operations. Backend layer: The core of the system, handling operations such as cluster/GPU management, client interaction, and automatic scaling. Database layer: stores and manages data, primary storage is used for structured data, and cache is used for temporary data. Task layer: manages asynchronous communications and tasks, ensuring efficiency of execution and data flow. Infrastructure layer: Infrastructure, including GPU pools, orchestration tools, and execution/ML tasks, equipped with a powerful monitoring solution.
4.5 IO Tunnels Utilize reverse tunneling technology to create a secure connection from the client to the remote server, allowing engineers to bypass firewalls and NAT for remote access without complex configuration. Workflow: IO Worker connects to the middle server (io.net server). The io.net server then listens for connections from IO Worker and engineer machines, facilitating data exchange via reverse tunneling.
Application in io.net Engineers connect to IO Workers through the io.net server, simplifying remote access and management without network configuration challenges. Advantages: Convenient access: Directly access IO Workers, eliminating network barriers. Security: Ensure protected communications and maintain data privacy. Scalability and flexibility: Efficiently manage multiple IO Workers in different environments.
4.6 IO Network Mesh VPN Network: Decentralized connectivity: Unlike the traditional star model, mesh VPNs connect nodes directly, providing enhanced redundancy, fault tolerance, and load distribution. Advantages: Strong resistance to node failures, strong scalability, low latency, and better traffic distribution.
Benefits of io.net: Direct connections reduce latency and optimize application performance. There is no single point of failure, and the network can still operate even if a single node fails. Enhance user privacy by making data tracking and analysis more challenging. The addition of new nodes does not affect performance. Resource sharing and processing are more efficient across nodes.
5. IO.NET Ecosystem and Halving Mechanism 5.1 Ecosystem GPU renters (also known as users), such as machine learning engineers who want to purchase GPU computing power on the IOG network. These engineers can use $IO to deploy GPU clusters, cloud gaming instances, and build Unreal Engine 5 (and similar) pixel streaming applications. Users also include individual consumers who want to perform serverless model inference on BC8.ai and the hundreds of applications and models that io.net will host in the future. GPU owners (also known as suppliers), such as independent data centers, crypto mining farms, and professional miners, want to make underutilized GPU computing power available on the IOG Network and profit from it. IO Coin holders (also known as the community) participate in providing cryptoeconomic security and incentives to coordinate mutual benefits and penalties between parties to promote the growth and adoption of the network.
5.2 Halving Mechanism 2024-2025: 6,000,000 $IO tokens will be released each year during these two years. 2026-2027: Starting in 2026, the annual release is halved to 3,000,000 $IO tokens. 2028-2029: The release amount continues to halve, with 1,500,000 $IO tokens released each year.
VI. Project Evaluation 6.1 Track Analysis io.net is a decentralized computing network based on the Solana blockchain, focusing on providing powerful computing power by integrating underutilized GPU resources. This project is mainly in the following track areas: 1. Decentralized Computing io.net has built a decentralized physical infrastructure network (Depin) that leverages GPU resources from different sources (e.g., independent data centers, crypto miners). This decentralized approach aims to optimize the utilization of computing resources and reduce costs while increasing accessibility and flexibility. 2. Cloud Computing Despite its decentralized approach, io.net provides services similar to traditional cloud computing, such as GPU cluster management and scalability for machine learning tasks. io.net aims to create an experience similar to traditional cloud services, but leverages the advantages of decentralized networks to provide more efficient and cost-effective solutions. 3. Blockchain Applications As a project based on blockchain technology, io.net uses the characteristics of blockchain, such as security and transparency, to manage resources and transactions in the network. Projects similar in functionality and goals to io.net include: Golem: It is also a decentralized computing network where users can rent or lease unused computing resources. Golem is committed to creating a global supercomputer. Render: Leverages decentralized networks to provide graphics rendering services. Render uses blockchain technology to enable content creators to access more GPU resources, thereby accelerating the rendering process. iExec RLC: This project creates a decentralized marketplace that allows users to rent out their computing resources. iExec supports various types of applications, including data-intensive applications and machine learning workloads, through blockchain technology.
6.2 Project Advantages Scalability: io.net specifically designed a highly scalable platform to meet the bandwidth needs of customers and enable teams to easily scale workloads across GPU networks without large-scale adjustments. Batch Inference and Model Serving: The platform supports parallel inference on data batches, allowing machine learning teams to deploy workflows on a distributed GPU network. Parallel training: To overcome memory limitations and sequential workflows, io.net leverages distributed computing libraries to parallelize training tasks across multiple devices. Parallel hyperparameter tuning: Exploiting the inherent parallelism of hyperparameter tuning experiments, io.net optimizes scheduling and search patterns. Reinforcement Learning (RL): Leveraging open source reinforcement learning libraries, io.net supports highly distributed RL workloads and provides a simple API. Instant Accessibility: Unlike the lengthy deployment of traditional cloud services, io.net Cloud provides instant access to GPU provisioning, enabling users to launch their projects in seconds. Cost efficiency: io.net is designed to be an affordable platform that is suitable for different categories of users. Currently, the platform is about 90% more cost-efficient than competing services, providing significant savings for machine learning projects. High security and reliability: The platform promises to provide first-class security, reliability, and technical support to ensure a safe and stable environment for machine learning tasks. Ease of implementation: io.net Cloud eliminates the complexity of building and managing infrastructure, enabling any developer and organization to seamlessly develop and scale AI applications.
6.3 Project Challenges 1. Technical complexity and user adoption Challenges: Although decentralized computing offers significant cost and efficiency advantages, its technical complexity may pose a large entry barrier for non-technical users. Users need to understand how to operate a distributed network and how to effectively utilize distributed resources. Impact: This could limit widespread adoption of the platform, especially among user groups less familiar with blockchain and distributed computing.
2. Cybersecurity and data privacy Challenges: While blockchain offers enhanced security and transparency, the open nature of decentralized networks can make them more vulnerable to cyberattacks and data breaches. Impact: This requires io.net to continuously strengthen its security measures to ensure the confidentiality and integrity of user data and computing tasks, which is key to maintaining user trust and platform reputation.
3. Performance and reliability Challenges: While io.net strives to provide efficient computing services through decentralized resources, coordinating between hardware resources in different geographical locations and of varying quality may pose performance and reliability challenges. Impact: Any performance issues caused by hardware mismatch or network latency may affect customer satisfaction and the overall effectiveness of the platform.
4. Scalability Challenge: Although io.net is designed to be a highly scalable network, in practice it is still a huge technical challenge to effectively manage and scale distributed resources around the world. Impact: This requires continued technical innovation and management improvements to keep the network stable and responsive in the face of rapidly growing user and computing demands.
5. Competition and market acceptance Challenges: io.net is not without competition in the blockchain and decentralized computing market. Other platforms such as Golem, Render, and iExec are also providing similar services, and rapid changes in the market may quickly change the competitive situation. Impact: To remain competitive, io.net needs to continuously innovate and improve the uniqueness and value of its services to attract and retain users.
VII. Conclusion The emergence of io.net fills the gap in the field of decentralized computing and provides users with a novel and promising computing method. With the continuous development of fields such as artificial intelligence and machine learning, the demand for computing resources is also increasing, so io.net has high market potential and value. On the other hand, although the market has given io.net a high valuation of $1 billion, its products have not been tested by the market, and there are uncertain risks in terms of technology. Whether it can effectively match its supply and demand relationship is also a key variable that determines whether its subsequent market value can reach a new high. From the current situation, the results of the io.net platform on the supply side have been initially shown, but the demand side has not been fully exerted, resulting in the current platform's overall GPU resources not being fully utilized. How to more effectively mobilize the demand for GPU resources is a challenge that the team must face. If io.net can quickly meet market demands and does not encounter or have major risks and technical problems during operations, with its AI+DePIN entity business attributes, its overall business will start the growth flywheel and become the most eye-catching project product in the Web3 field. This also means that io.net will be a high-quality investment target for the branch. Let us continue to follow up, observe and verify carefully. |
