bzCompute

bzCompute is a computation graph library with built-in support for domain-decomposition and prallel computation. The library can be used for expressing and executing large number of mathematical and text-processing operations using Data-Flow graphs, (Educational version of tensorflow), written in pure python code with numpy support.

Examples :

The educational project supports limited number of text-processing and mathematical operations that are normally used frequently. Look at examples folder for various examples

Parallel Computation :

The librabry supports both sequential and parallel computation on graphs. Domain Decomposition is the computation technique used to provide task-level parallelism by creating replicas of computation graphs . The library creates a Master-worker setup, where the MasterSession creates specified number of worker sessions, each worker-session is a thread. These threads can be pre-forked to memory or can be created on demand. Each worker is automatically assigned a name. The results are collected. Domain decomposition is manily used for running multiple replicas of data-flow graphs on different inputs, check out examples.

Supported Sessions :

The library supports three types of sessions as of now :

• SequentialSession : SequentialSession executes computation graph in a sequential order, leaving parallelism to OS and Hardware.
• MasterSession : Creates a master session for parallel computation, can be used for domain-decomposition, by specifying number of worker threads.
• StringSession : It is a variant of SequentialSession for executing a computation graph composed of strign operations.

Supported Operations :

bzCompute supports many operations as of now, the library also provides support for defining custom operations as per the requirements.

Numerical Operations :

Look at pyCompute/KernelOperations.py to obtain list of all supported operations

Text-Processing Operations :

Look at pyCompute/text_processing/StringOperations.py for all supported string operations.