Blendr,
the Blueprint
for tomorrow

Secure, scalable access to computing resources via blockchain for research and development.
Documentation

Elevate your AI, rendering, and simulations with Blendr

For AI, rendering, and simulations, Blendr offers high-performance computing sans centralized costs and scalability limits. Optimize resource usage, minimize expenses, and maintain uninterrupted productivity.
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  • BCM

    Decentralized GPU
    Compute Mesh (BCM)

    Blendr's BCM effectively aggregates underutilized GPU resources across a global network. This network optimally distributes computational tasks, ensuring each GPU's capacity is utilized efficiently, thereby providing a scalable solution for demanding rendering tasks and Al computations without the overhead associated with traditional cloud computing services.
  • DARL

    Blockchain-Enabled Digital Rights Management (DARL)

    Blendr incorporates granular digital rights management through its DARL system. This leverages the immutability and transparency of blockchain to offer on-chain traceability for digital assets, ensuring creators maintain control over their work and receive fair compensation.
  • Efficient Resource Allocation

    Dynamic Task Assignment

    Blendr's algorithms dynamically allocate computing tasks among available GPU nodes based on resource availability and performance metrics. This intelligent resource allocation minimizes waste, maximizes system throughput, and optimizes cost-effectiveness for users.
Coming Soon

Blendr
Box X1

A cutting-edge, plug-and-play solution that allows users to host a $BLENDR node at home, enhancing the decentralized GPU network and offering passive income opportunities. Compact and powerful, it's your gateway to advanced rendering and AI computing.

Blendr Box X1 Specifications

  • Equipped with RTX 4060* for optimized processing in complex tasks.
  • M.2 SSD support ensures rapid data handling.
  • Thunderbolt™ 4 for speedy transfers up to 40Gbps and connecting high-performance devices.
  • TPM 2.0 for enhanced data security.
  • Compliant with CE, FCC, KC, RoHS standards.
  • Ultra-compact 3.5” form factor for space efficiency.
*Specifications, including the GPU, are based on our current prototype and might change to optimize performance.

Join our GPU sharing network and earn $BLENDR tokens

for powering rendering and computational tasks
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  • Internet of GPUs

    Elevate your projects with our Plug-and-Play Rendering and AI Computing Solution

  • Optimized Rendering Grids

    Integrate your workflows with our Decentralized Processing Infrastructure Network, DePIN
    Learn More
  • Distributed
    Computing
    Adaptive
    Expansion
    Universal
    Access
    Versatile
    Solutions
    Fortified
    Transactions
    Steadfast
    Performance
    Community
    and Support
    Economic
    Advantage

  • Flexible Payment Gateway

    Diverse and secure payment methods tailored to your convenience

MVP Development Roadmap

Establish a functional prototype that allows GPU owners to offer their computing power and users to execute tasks using available GPU resources.

Phase 1

Initial MVP Setup

Client-Side Python Program (CLI)

Purpose:

Enables GPU owners to register their devices with the central server and listen for incoming tasks.

Features:

  • Detect local GPU resources.
  • Establish WebSocket connections to the central server for real-time communication.
  • Receive task details and execute tasks using the GPU.

Central Server

Technology:

Enables GPU owners to register their devices with the central server and listen for incoming tasks.

Features:

  • Manage user registrations and authentications.
  • Handle task dispatching and monitor GPU availability.
  • Provide a WebSocket endpoint for client communications.

Web Dashboard

Purpose:

Allows users to view available GPU resources and submit tasks.

Features:

  • Display overall GPU capacity or specific available GPUs (configurable based on feedback).
  • User interface for submitting tasks and viewing task status.

Data Management with AWS S3

Implementation:

Utilize S3 for storing input datasets and processed results.

Features:

  • Generate and manage S3 access keys to allow users direct access to upload and download data, reducing load on the central server.

Phase 2

Scale and Decentralize

Decentralized Storage System

Purpose:

Replace S3 with a decentralized storage solution to enhance privacy and reduce reliance on centralized services.

Plan:

  • Research and integrate technologies like IPFS (InterPlanetary File System) or similar for storing and retrieving task data.

Token-Based Economy

Purpose:

Introduce a blockchain-based token system to reward users based on the GPU power they provide.

Implementation:

  • Develop and deploy smart contracts on a blockchain platform.
  • Implement a system for tracking resource usage and issuing tokens accordingly.

Phase 3

Advanced GPU Integration

Distributed GPU Processing

Goal:

Enable multiple GPUs to work together on complex tasks, enhancing processing capabilities and efficiency.

Challenges:

Address synchronization, data consistency, and network latency.

Approach:

Utilize advanced distributed computing frameworks and modify the client software to support distributed tasks.

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