Lightning Network Node RAM/CPU: Is The CmRat Enough?
- Published on
- Guides
Setting up a domestic Lightning Network (LN) node can be both exciting and rewarding, especially if you’re taking advantage of modular systems like the CmRat.
But before you jump in, it’s worth thinking about the kind of hardware you’ll need, particularly the compute module (CM) you choose. The CmRat supports a variety of modules, each with unique specs that impact performance. This allows you to select or upgrade the compute module later as needed, depending on whether you require higher performance or not.
Supported Compute Modules
As of now, the CmRat supports several modules, including:
- Radxa CM3
- Raspberry CM4
- Radxa CM5 Lite
- Raspberry CM5
- Radxa CM5
First of all, it’s important to node that each of these node will let you run a lightning network smoothly. It’s important to note however, that each module has different versions, as it varies in internal memory, RAM, and additional features like Wi-Fi and Bluetooth. These specs will influence your node’s ability to handle LN traffic efficiently.
What RAM and CPU Trim Do You Need?
The amount of RAM and CPU power required depends on the workload your node will handle. A Lightning node with only a handful of channels won’t demand much, but a node with many active channels and high traffic will require more resources.
RAM
- RAM: Most compute modules come with trims ranging from 1 GB to 8 GB or more. A Lightning node with fewer than 20 channels can typically run smoothly with 2 GB of RAM. However, for nodes exceeding 100 channels or handling frequent transactions, 4 GB or more is recommended.
CPU (Compute Module)
The CmRat supports a variety of compute modules, each with unique CPU capabilities. Here’s a breakdown to help you choose the right module for your Lightning Node based on channel counts and routing expectations:
1. Radxa CM3
- CPU: Rockchip RK3566, Quad core Cortex-A55 (ARM v8) 64-bit SoC @ 2.0GHz.
- Best For: Basic setups with up to 50 channels. The 1.8 GHz quad-core processor provides sufficient power for light to moderate usage.
2. Raspberry CM4
- CPU: Quad-core Cortex-A72, 1.5 GHz.
- Best For: Small to mid-sized nodes (up to 100 channels). The Cortex-A72 architecture is efficient and well-suited for nodes handling moderate routing activity.
3. Radxa CM5 Lite
- CPU: Rockchip RK3588S octa-core processor with 4x Cortex‑A76 cores @ up to 2.4GHz.
- Best For: Mid-tier setups (50–200 channels). This module balances power and efficiency, making it a good choice for nodes that require faster routing capabilities.
4. Raspberry CM5
- CPU: 2.4GHz quad-core Cortex-A76 CPU.
- Best For: Mid to high-tier setups (100–250 channels). While it isn’t officially out yet, early specs suggest it will handle high traffic with ease.
5. Radxa CM5
- CPU: Rockchip RK3588S processor, featuring an octa-core CPU, Mali-G610 MP4 GPU, and up to 16GB LPDDR4x RAM.
- Best For: High-performance nodes (200+ channels). The powerful Cortex-A76 cores make this module a great option for nodes handling frequent routing and high traffic volumes.
Extra: Storage
To operate a Lightning node on the CmRat, you’ll need at least 2TB of NVMe storage. A Bitcoin node alone takes up nearly 1TB, while an Electrum server like Fulcrum exceeds 100GB. Adding the OS and apps like LND pushes storage requirements to 1.2–1.3TB, making 2TB the ideal standard.
For other components to customize your CmRat, read our comprehensive guide:
Core Lightning vs. LND: Resource Consumption
Your choice of software significantly impacts resource usage. Here’s how the two popular implementations compare:
- Core Lightning (CLN): Lightweight and efficient. CLN is modular by design and only runs the components you need. This means lower CPU and RAM usage, making it an excellent choice for smaller setups or limited hardware.
- LND: More feature-rich but heavier. LND has higher RAM and CPU demands, which might be overkill for modest setups but useful if you need advanced features.
Estimated Resource Consumption
Here’s a rough guide to RAM usage for each implementation (OS and other apps excluded):
| Channels | Core Lightning RAM | LND RAM |
|---|---|---|
| 10 Channels | ~100 MB | ~150 MB |
| 50 Channels | ~300 MB | ~500 MB |
| 100 Channels | ~700 MB | ~1 GB |
| 200+ Channels | ~1.5 GB | ~2+ GB |
CPU consumption scales similarly. Core Lightning’s efficiency keeps CPU usage manageable, even for nodes with a moderate number of channels.
Hardware Recommendation
For most hobbyists or home setups, here’s what works well with our CmRat Carrier Board:
1. Minimal Setup (1–50 Channels):
- CM: Radxa CM3 or Raspberry CM4
- RAM: 2–4 GB
- CPU: Quad-core, ~1.5 GHz
2. Mid-Tier Setup (50–200 Channels):
- CM: Radxa CM5 Lite or Raspberry CM5
- RAM: 4–8 GB
- CPU: Quad-core, ~1.8 GHz
3. High-Performance Setup (200+ Channels):
- CM: Radxa CM5
- RAM: 8+ GB
- CPU: Multi-core, ~2 GHz or higher
Example: Calculating Resource Needs
Let’s say you’re running a node with 75 channels:
- Using Core Lightning, expect about 500 MB of RAM usage and a CPU requirement of ~10–15% on a 1.5 GHz core.
- With LND, the RAM usage might increase to ~700 MB, with CPU demands rising to ~20–25% on the same hardware.
If you plan to scale, consider future-proofing with a compute module that has at least 6–8 GB of RAM.
Final Thoughts
The CmRat is more than capable of supporting a Lightning node, provided you match the compute module to your expected workload. Core Lightning is a better choice if you’re looking to minimize resource consumption, while LND might be worth it if you need its extra features.
With careful planning, the CmRat and a suitable compute module can keep your node running smoothly, whether you’re routing a few transactions or managing a bustling hub.
