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## rabit: Reliable Allreduce and Broadcast Interface
rabit is a light weight library that provides a fault tolerant interface of Allreduce and Broadcast. It is designed to support easy implementation of distributed machine learning programs, many of which sits naturally under Allreduce abstraction.
rabit is a light weight library that provides a fault tolerant interface of Allreduce and Broadcast. It is designed to support easy implementations of distributed machine learning programs, many of which fall naturally under the Allreduce abstraction.
* See the [package interface file](src/rabit.h)
Features
====
* Portable library
- Rabit is a library instead of framework, program only need to link the library to run, without restricting to a single framework.
- Rabit is a library instead of a framework, a program only needs to link the library to run, without restricting to a single framework.
* Flexibility in programming
- Programs call rabit functions in any sequence, as opposed to defines limited functions and being called.
- Program persist over all the iterations, unless it fails and recover
- Programs can call rabit functions in any sequence, as opposed to frameworks where callbacks are being offered and are called by the framework, i.e. inversion of control principle.
- Programs persist over all the iterations, unless they fail and recover
* Fault tolerance
- Rabit program can recover model and results of syncrhonization functions calls
- Rabit programs can recover the model and results from synchronized function calls
* MPI compatible
- Codes using rabit interface naturally compiles with existing MPI compiler
- User can fall back to use MPI Allreduce if they like with no code modification
- Code that uses the rabit interface also compiles with existing MPI compilers
- Users can use MPI Allreduce with no code modification
Design Note
Design Notes
====
* Rabit is designed for algorithms that replicate same global model across nodes, while each node operating on local parition of data.
* The global statistics collection is done by using Allreduce
* Rabit is designed for algorithms that replicate the same global model across nodes, while each node operates on a local partition of the data.
* The collection of global statistics is done using Allreduce
Design Goal
Design Goals
====
* rabit should run fast
* rabit is light weight
* rabit dig safe burrows to avoid disasters
* rabit should be light weight
* rabit should safely dig burrows to avoid disasters