Ray 0.8.0 Release Notes
- Add remaining features from old dashboard
- Add Ray Kubernetes Operator with readme, structure, config and CRD related files
- Add example and tutorial for DCGAN
- Add support for multi-model multi-optimizer training in sgd
- Add deadline awareness to serve
- Add streaming data transfer and python integration
- Return parameters for a command in projects
- Enable gRPC direct calls by default for tasks and actors, allowing direct task submission between workers and between actors over gRPC while the Raylet only coordinates scheduling and creation decisions
- Inline small objects (less than 100KB in size) into task submissions and returns instead of placing them in the object store
- Report trials by state fairly in Tune
- Ensure numpy >= 1.16.0 is installed for fast pickling support
- Avoid workers starting with the same random seed
- Properly handle a forwarded task that gets forwarded back
- Remove the extra 0.5 in the Diagonal Gaussian entropy in RLlib
- Fix bug in PBT where initial trial result is empty
Ray 0.8.0 Release Notes
This is the first release with gRPC direct calls enabled by default for both tasks and actors, which substantially improves task submission performance.
Highlights
- Enable gRPC direct calls by default (#6367). In this mode, actor tasks are sent directly from actor to actor over gRPC; the Raylet only coordinates actor creation. Similarly, with tasks, tasks are submitted directly from worker to worker over gRPC; the Raylet only coordinates the scheduling decisions. In addition, small objects (<100KB in size) are no longer placed in the object store. They are inlined into task submissions and returns when possible.
Note: in some cases, reconstruction of large evicted objects is not possible with direct calls. To revert to the 0.7.7 behaviour, you can set the environment variable RAY_FORCE_DIRECT=0.
Core
- [Dashboard] Add remaining features from old dashboard (#6489)
- Ray Kubernetes Operator Part 1: readme, structure, config and CRD realted file (#6332)
- Make sure numpy >= 1.16.0 is installed for fast pickling support (#6486)
- Avoid workers starting with the same random seed (#6471)
- Properly handle a forwarded task that gets forwarded back (#6271)
RLlib
- (Bug Fix): Remove the extra 0.5 in the Diagonal Gaussian entropy (#6475)
- AlphaZero and Ranked reward implementation (#6385)
Tune
- Add example and tutorial for DCGAN (#6400)
- Report trials by state fairly (#6395)
- Fixed bug in PBT where initial trial result is empty. (#6351)
Other Libraries
- [sgd] Add support for multi-model multi-optimizer training (#6317)
- [serve] Added deadline awareness (#6442)
- [projects] Return parameters for a command (#6409)
- [streaming] Streaming data transfer and python integration (#6185)
Thanks
We thank the following contributors for their work on this release:
@zplizzi, @istoica, @ericl, @mehrdadn, @walterddr, @ujvl, @alindkhare, @timgates42, @chaokunyang, @eugenevinitsky, @kfstorm, @Maltimore, @visatish, @simon-mo, @AmeerHajAli, @wumuzi520, @robertnishihara, @micafan, @pcmoritz, @zhijunfu, @edoakes, @sytelus, @ffbin, @richardliaw, @Qstar, @stephanie-wang, @Coac, @mitchellstern, @MissiontoMars, @deanwampler, @hhbyyh, @raulchen