Tinychain

Latest version: v0.17.0

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0.17.0beta

Changelog:
- remove the cross-service transaction protocol's requirement for bidirectional synchronization messages
- break the startup process into multiple stages
- allow partial replication without joining a cluster
- implement support for local peer discovery via mDNS
- upgrade to hyper 1.4
- require a correct cluster state hash to join a cluster
- gate `Chain` and each `Collection` type with a feature flag for fast debug builds
- separate the `tc_server` sub-crate from the main crate

0.16.0beta

Changelog:
- validate auth tokens exactly once, upon receipt
- reject unauthorized requests without reading payload data (headers only)
- remove unnecessary lock acquisitions when instantiating a new request handler
- move per-transaction garbage collection completely into a background task
- separate a new `tinychain_async` package out of the `tinychain` Python client
- move client implementations into a single `client` directory

0.15.0beta

Changelog:
- improved OpenCL support & performance

This release re-introduces a separate binary which supports GPU acceleration via OpenCL.

0.14.0beta

Changelog:
- improved table table index merge performance
- improved memory performance by minimizing heap allocations

0.13.1beta

This release includes incremental bug fixes and performance improvements focused on supporting high-traffic applications.

0.13.0beta

Version 0.13-beta introduces experimental support for multi-GPU hardware acceleration using the [ha-ndarray](https://github.com/haydnv/ha-ndarray) library. If you are using TinyChain, we want to hear from you! Send an email with the word "hello" to [hellotinychain.net](mailto:hellotinychain.net).

Changelog:
* dropped ArrayFire as a dependency
* added experimental support for multi-GPU hardware acceleration (build with the "opencl" feature flag to enable this)
* updated collection types to implement a log-structured merge consistency model, for faster commits
* decoupled transactional locks from filesystem locks
* added support for cell level locking
* added support for multiple axes in tensor reduce operations (including einsum)
* updated crate structure to include the new `chain`, `collection`, `fs`, `scalar`, and `state` sub-crates for faster build times

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