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Tips & Tricks

Additional Tips​

Welcome to the Additional Tips section! Whether you're a seasoned farmer or just starting out with the Autonomys Network, these tips and tricks are designed to enhance your experience and efficiency. Here, we delve into practical advice and lesser-known techniques to help you fine-tune your farming setup and navigate common challenges with ease. From configuring your environment to managing background processes, these insights are tailored to ensure your Farmer operates smoothly and effectively. Let's dive in and explore how you can get the most out of your Autonomys Network Farmer.

Switching to a new snapshot from older/different versions of Autonomys​

info

Unless specifically mentioned by the Development team you should NOT have to wipe your configuration on new releases.

In general you should be able to download the latest release, and re-start the Node & Farmer with the same commands as you started to prior version with no errors.

There are some cases where version updates will cause issue with your Node & Farmer and you may have to wipe your node, typically when errors occur. If you have any issues you can always check our Forums and hop in our Discord Server to ask for help.

Wipe​

If you were running a node previously, and want to switch to a new network, please perform these steps and then follow the guide again:

Replace these placeholders
  • <PATH_TO_FARM>: Path to your farm directory
  • <BASE_PATH>: Path to your node data directory
./subspace-farmer-ubuntu-x86_64-skylake-mainnet-2025-aug-20 wipe <PATH_TO_FARM>
./subspace-node-ubuntu-x86_64-skylake-mainnet-2025-aug-20 wipe <BASE_PATH>

Now follow the installation guide from the beginning.

Utilizing Multiple Disks​

To maximize storage capabilities, you can engage multiple disks directly. This is often more efficient than relying on RAID configurations:

Replace these placeholders
  • <REWARD_ADDRESS>: Your wallet address for farming rewards
./subspace-farmer-ubuntu-x86_64-skylake-mainnet-2025-aug-20 farm --reward-address "<REWARD_ADDRESS>" \
    path="/media/ssd1,size=4TiB" \
    path="/media/ssd2,size=8TiB"

Optimizing DSN Syncing​

note

The DSN can be a nuanced topic, to better understand our Decentralized Storage Network, please refer to this guide from our Academy.

Parameters to Use with Caution
--out-peers
--in-peers
--dsn-target-connections
--dsn-pending-in-connections
--dsn-in-connections

The default parameters are set with the capabilities of common consumer modem/routers in mind. Adjusting certain parameters could enhance DSN sync performance by increasing parallelism. However, if you decide to increase them significantly, ensure that your modem/router is performant enough to handle the increased traffic. Node:

--dsn-out-connections
--dsn-pending-out-connections

Farmer: Increasing the values of the farmer parameters could increase the plotting speed.

--out-connections
--pending-out-connections

Help​

Both the node and the farmer have a variety of flags and parameters. To see a full list, append the --help flag to either the node or the farmer command.

Some Additional Tips for Node, Farmer and Docker​

Plotting concurrency (CPU only)​

During plotting, there are both parallel and sequential parts of the table generation. By generating several tables simultaneously, we can overlap the sequential parts with parallel parts, thus improving CPU utilization. While generating tables for all records requires significant RAM, producing tables for only a few records at a time offers an optimal balance between CPU and RAM usage. We added the --cpu-record-encoding-concurrency option to override the default behavior, which allocates one record for every two cores but does not exceed eight in parallel. According to our internal testing with P-cores, E-cores, and combinations of P+E cores, this setting appears to achieve peak performance. If you prefer to use the previous behavior, or if your RAM usage becomes too high, you can set --cpu-record-encoding-concurrency to 1. You may also experiment with setting it to 2, 3, etc., which may yield better results depending on your specific CPU/RAM configuration.

Create Missing Farms​

A farmer has the option to specify whether the system should automatically create missing farms upon startup. If you provide a path to a farm that isn't found, the system will generate a new one. However, this may not be desirable if a drive fails to mount properly. By default, this option is set to true, but you can override it by adding --create false. Setting this flag to false after establishing your farms can prevent unintentional file writes to the wrong drive.

Record Chunks Reading Mode​

Upon startup, each farm will benchmark the performance to identify the most efficient proving method, yielding either ConcurrentChunks or WholeSector results. If you already know the optimal method for your setup, you can specify it as an argument for each farm to save time benchmarking.

Replace these placeholders
  • <PATH_TO_FARM>: Directory where you want to store the farm
  • <FARM_SIZE>: Amount of space allocated for farming (e.g. 4TiB, 8TiB)
  • <RECORD_CHUNKS_MODE>: Either ConcurrentChunks or WholeSector

For example, you can include record-chunks-mode= after defining the path and size, assigning the desired value, e.g., path=<PATH_TO_FARM>,size=<FARM_SIZE>,record-chunks-mode=<RECORD_CHUNKS_MODE>. If you do not provide this parameter, the system will benchmark each disk on startup to identify the most efficient method.

Benchmarking Your Farmer​

Benchmarking helps you test the plotting speed of your farmer against different versions of the Autonomys Network.

./subspace-farmer-ubuntu-x86_64-skylake-mainnet-2025-aug-20 benchmark audit <PATH_TO_FARM>
tip

Replace <PATH_TO_FARM> with the actual path to your farm.

This will provide you with metrics and insights regarding plotting performance.

At the moment, Autonomys Node supports rayon implementation mechanism, that opens files as many times as there are farming threads and, for each thread, uses a dedicated file handle.

To interpret the results: typically, you assess throughput to determine the maximum auditable size across any number of disks. Both CPU and disk performance influence this metric.

To read more about audit benchmarking, read this forum post.

There is a second command available, which helps you determine how much time your farmer has after auditing to provide proof.

./subspace-farmer-ubuntu-x86_64-skylake-mainnet-2025-aug-20 benchmark prove <PATH_TO_FARM>

Each farmer has ~4 seconds to audit and prove, so depending on how fast auditing is, the remaining time will be used for proving. Proving performance doesn't depend on the farm size.

If an environment does not have enough time for the proving step, a message such as this is logged by the farmer:

Proving for solution skipped due to farming time limit slot=6723846 sector_index=46

To read more about prove benchmarking, read this forum post.

Scrubbing Your Farmer​

In certain situations, especially when the farmer terminates unexpectedly or encounters an error, it might fail to restart correctly. The scrub command assists in resolving such issues by cleaning or resetting the specified farm.

./subspace-farmer-ubuntu-x86_64-skylake-mainnet-2025-aug-20 scrub <PATH_TO_FARM>
tip

Replace <PATH_TO_FARM> with your actual farm path.

Use this command cautiously as it modifies the farm state to recover from errors.

Specify Exact CPU Cores for Plotting/Replotting (CPU only)​

This option will override any custom logic that the subspace farmer might otherwise use. You can specify the plotting CPU cores by adding --cpu-plotting-cores, followed by the desired cores parameters. Cores should be listed as comma-separated values, with whitespace used to separate different thread pools or encoding instances. For example, --cpu-plotting-cores 0,1 2,3 will result in two sectors being encoded simultaneously, each using a pair of CPU cores.

Similarly, you can customize the replotting CPU cores using --cpu-replotting-cores, followed by arguments similar to those used in the --cpu-plotting-cores example above.

Note that setting --cpu-plotting-cores requires --cpu-replotting-cores to be configured with the same number of CPU core groups. If the --cpu-replotting-cores setting is omitted, the node will default to using the same thread pool as for plotting.

Timekeepers​

Proof-of-Time is secured by Timekeepers, an optional role that has been added to the node. Timekeepers help run PoT to ensure the security of the network. Timekeeping requires a high-performance core CPU but can be undertaken by any node runner. You can enable timekeeping with the following commands.

  • --timekeeper: To enable timekeeping on the node
  • --timekeeper-cpu-cores: To specify which cores the Timekeeper will run on.

Read more about Timekeepers

Common Command Examples​

For both the node and the farmer, here are some frequently used commands:

Replace these placeholders

  • <PATH_TO_FARM>: Path to your farm directory

  • <BASE_PATH>: Path to your node data directory

  • Display farm information: ./subspace-farmer info <PATH_TO_FARM>

  • Scrub the farm for errors: ./subspace-farmer scrub <PATH_TO_FARM>

  • Erase all farmer-related data: ./subspace-farmer wipe <PATH_TO_FARM>

  • Erase all node-related data: ./subspace-node wipe <BASE_PATH>

NUMA Support​

note

NUMA support will benefit farmers with large, powerful CPUs and lots of RAM available. The required RAM amount depends on the processor and the number of threads.\

Previously plotting/replotting thread pools were created for each farm separately even though only a configured number of them can be used at a time (by default just one). With the introduction of NUMA support, the farmer application has a thread pool manager that will create a necessary number of thread pools that will be allocated to currently plotting/replotting farms. When a thread pool is created, it is assigned to a set of CPU cores and will only be able to use those cores. Pinning doesn’t pin threads to cores 1:1, instead, the OS is free to move threads between cores, but only within CPU cores allocated for the thread pool. This will ensure plotting for a particular sector only happens on a particular CPU/NUMA node.

Enabling NUMA on Windows/Linux machines​

On Linux and Windows, the farmer will detect NUMA systems and create a number of thread pools that correspond to the number of NUMA nodes. This means the default behavior will change for large CPUs and consume more memory as a result, but that can be changed to the previous behavior with CLI options if desired. To use NUMA, you need to enable it via the BIOS of your motherboard for the farmer to know it exists. This option is present in motherboards for Threadripper/Epyc processors but might exist in others too. If you don’t enable it, both OS and farmer will think you have a single UMA processor and will not be able to apply optimizations.

To read more about NUMA support and the benefits it provides for large CPUs read this forum post.

Changing number of open files limit (Linux)​

Changing the number of open files limit on Linux is sometimes necessary for both system and application performance tuning. Applications that manage file sharing or distribution, including peer-to-peer systems, may require opening numerous connections to different peers simultaneously. A higher open files limit allows these applications to maintain more connections, improving data transfer rates and system efficiency.

This can also help to mitigate the Too Many Open Files error.

You can use the ulimit command to change the limit for open files temporarily. For example, setting ulimit -n 2048 will set the limit to 2048. This change is reverted after logging out or a reboot.

For a permanent change, you have two approaches:

  • To modify the kernel parameter fs.file-max. You can do this using the sysctl command sysctl -w fs.file-max=500000.
  • To set limits for individual users, you need to edit the /etc/security/limits.conf file. You can specify hard and soft limits for the number of open files username soft nofile 10000 for the soft limit and username hard nofile 30000 for the hard limit.