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Releases: Lumenaut-Network/tools

Version 2.0 (Stable)

27 Dec 13:59
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This version is well tested and decently optimized. It parallelizes transactions using payment channels and produces very detailed output results. It's especially resilient against congested network state, which would only result in a longer time to process payments.

This version supports up to 20 parallel channels, which can be set up using the tool's Settings UI. This will be dropped in the future, using a JSON config file.

Performance: ~8000 inflation payment operations per minute with 20 payment channels

Noteworthy changes:

  • Dropped the ability to fetch data from Fed.network, this version now requires you to run your own Horizon/Stellar Core node and interface directly with their databases.
  • Dropped ability to paste arbitrary data into several of the input windows, the amount of data in JSON format was unbearable for the poorly optimized UI framework (this release is working towards full automated back-end processing, and away from manual operations. This version of the tool does not allow you to recover from partial payments anymore. This version is resilient to everything but power-loss mid payment. We're working on a new disaster recovery approach geared towards back-end operations rather than manual intervention.

Version 1.0 (Stable)

06 Jul 13:09
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This version is well tested but not optimized (uses a lot of memory due to constant conversion between run-time data and JSON, which we could get away with until the number of voters grew). Well suited for pools with a maximum of 100k voters or less, at which point the computation and memory requirements start to be a nuisance.

This will be the last version that will support fetching data from Fed.Network. From this point on the manager will require a local Horizon Node to minimize the data transformation and will support multi-channel processing for inflation payments in order to scale up to millions of voters and still manage distributing payments within an hour from inflation payment.