Andrey Kramerov
|
March 3, 2025
|

Your IO.net Guide to GPU Cloud & Hardware Innovation

High-performance computing requires high-powered GPUs, but traditional cloud providers like AWS and Google Cloud have high costs, startup delays, and centralization constraints.

That’s where IO.net changes the game. As a decentralized, GPU-powered cloud, IO.net provides a faster, more affordable, and globally distributed alternative. Whether you're training AI models, running complex simulations, or optimizing cloud costs, IO.net gives you computing power when needed — without the usual limitations.

Here’s how IO.net is transforming cloud computing.

1. IO Explorer: Your Control Center for Computing Power

IO Explorer is the central hub for managing your GPU and CPU resources. It provides real-time tracking, cost estimation, and resource allocation tools to help you optimize performance efficiently.

Key Features at a Glance

Feature What It Does
Real-Time Job Tracking Monitor job status (queued, running, completed) and resource usage.
Resource Explorer Filter available GPUs/CPUs by specs (VRAM, cores, location, price)
Performance Dashboards View GPU utilization, memory consumption, and network latency.
Billing Insights Track costs and earnings in $IO tokens.

What You Can Do with IO Explorer

  • Select the proper hardware for compute-intensive tasks.
  • Track workloads in real-time through an activity stream.
  • Compare GPU cluster pricing to optimize spending.
  • Receive notifications when jobs are completed or require adjustments.

For a detailed walkthrough, check out our IO Explorer Guide.

2. Decentralized vs. Centralized GPU Clouds: What’s the Difference?

Most cloud computing services rely on large, centralized data centers owned by major tech companies. IO.net takes a decentralized approach, allowing users to access GPU power worldwide.

Decentralized GPU Clouds (IO.net’s Approach)

IO.net’s peer-to-peer computing model aggregates unused GPU resources from a global network. This approach provides:

  • Flexible, on-demand access to high-performance GPUs.
  • Lower costs by bypassing expensive data center overhead.
  • Scalability without the hardware limitations of centralized providers.

Centralized GPU Clouds (AWS, Google Cloud, Azure)

Traditional cloud providers operate closed, centralized networks with:

  • Limited GPU availability due to hardware scarcity.
  • Higher costs for enterprise-level compute power.
  • Longer setup times compared to decentralized alternatives.

For a deeper dive into IO.net’s decentralized vs. centralized GPU infrastructure, visit our technical documentation.

3. Supported Hardware: Is It Alright to Bring Your Device?

One of IO.net’s key advantages is hardware flexibility. You can bring your own GPU or CPU, allowing you to sell unused compute power when your system is idle.

GPU Compatibility

Tier Examples Best For
Consumer NVIDIA RTX 3090/4090, AMD Radeon RX 7900 Rendering, light AI training
Prosumer NVIDIA RTX A6000, AMD Radeon Pro W6800 Mid-scale ML, simulation
Enterprise NVIDIA A100/H100, AMD Instinct MI250X Large LLM training, HPC workloads

CPU Compatibility

Architecture Examples Recommended Use
x86 Intel Xeon, AMD EPYC General-purpose computing
ARM AWS Graviton, Ampere Altra Energy-efficient workloads

Tips for Optimal Performance

  • Use wired Ethernet for lower latency and more stable connections.
  • Optimize power settings to maintain consistent performance.

Refer to our Supported Devices list for a complete list of compatible devices.

4. Spin Up Powerful GPUs & CPUs in Minutes with IO Cloud

Need serious computing power fast? With IO Cloud, you can launch GPU- and CPU-powered virtual machines (VMs) or containers in minutes—perfect for AI model training, deep learning, and anything else that eats up compute power. No long setup, no waiting around—just raw power when you need it.

VMs vs. Containers: Which One’s Right for You?

Not sure whether to go with a VM or a container? Here’s a quick breakdown:

  • Virtual Machines (VMs) – Your own isolated environment with a dedicated OS. Great for heavy workloads, security, and full customization.
  • Containers – Lightweight, fast, and share the host OS. Perfect for quick deployments, microservices, and scaling AI workloads efficiently.
Feature VMs Containers
Overhead Higher (requires full OS) Lower (uses shared kernel)
Isolation Strong (hypervisor-based) Moderate (namespace separation)
Boot Time 1–2 minutes Seconds
Best For Legacy applications, multi-tenant environments Microservices, CI/CD pipelines

How to Get Started with IO Cloud

  1. Create a virtual machine through the IO.net website or API.
  2. Choose the proper GPU for your workload.
  3. Monitor instances in real-time to ensure optimal performance.

Need assistance installing your very first VM? Review our IO Cloud Deployment Guide.

Why IO.net Stands Out

Cost Savings

Reduce cloud computing costs by leveraging a global network of underutilized GPUs.

Power & Flexibility, Your Way

Pick the exact GPU power you need—whether it’s a high-end consumer GPU, a prosumer workhorse, or enterprise-grade muscle. No overpaying, no wasted resources—just what fits your workload.

Earn While Cutting Down on E-Waste

Got extra GPU power sitting around doing nothing? Put it to work. Rent out unused devices, earn passive income, and help reduce e-waste at the same time. Win-win.

Ready to Build Something Awesome?

We can help get you started - look on the Documentation page for setup guides, API references, and troubleshooting tips.

Join the movement for decentralized cloud computing today and start scaling your workloads with faster, more affordable compute power. 🚀  Start Building on IO.net

Disclaimer: The information provided on this page is for general informational purposes only and does not constitute legal, financial, or professional advice. Any statements regarding the company’s plans, future expectations, or projections are forward-looking and subject to change at any time without prior notice. No information herein creates any legal obligations, warranties, or guarantees.

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