v0.1.1

What's Changed

• New Worker and Validator Executables: Introduced executables for UNIX systems. [#16]
• Idle GPU Mining: Workers can now execute GPU mining scripts (or other intensive tasks) when idle.
  • Mining scripts are only executed as root if the main logic is also run as root (not recommended). [#20]
• Configurable Mining: A config.json file attached with the miner binary allows users to specify worker addresses and mining file paths.

Limitations

• General Issues: Bugs, performance hiccups, and limited network availability are expected in this early release.
• Model Support:
  • Tensorlink supports scriptable PyTorch models (torch.jit.script) and select open-source Hugging Face models (excluding API-key-dependent models).
  • This is due to security and serialization constraints in untrusted P2P interactions. We're working on custom serialization methods to support all PyTorch model types. [#14]
• Model Size: Current public jobs are best suited for models under ~1 billion parameters.
• Worker Allocation: Public jobs are limited to one worker.
  • Data-parallel acceleration is disabled for public tasks but can be enabled for local jobs or private clusters.
• Latency: Internet speeds and latency may impact performance, particularly for complex tasks.

Future Plans

• Expanded Capacity: We're actively scaling the network, with the next update set to support larger models and enable more complex workflows.
• Enhanced Model Support: Improvements in serialization methods will unlock broader compatibility for all PyTorch model types.
• Worker Allocation Updates: Future releases will improve worker distribution for public jobs, allowing for more robust task execution.