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Distributed Matrix Multiplication

This project involves the use of REST interface and gRPC based services to allow matrix multiplication to be split among multiple machines. Block Matrix multiplication is a method for multiplying matrices which is useful in distributed systems as it can easily split the calculations among mutiple machines.

Architecture

  • This project involves 3 components
    • a REST interface to upload matrix as input files. I'm using FastAPI for this.
    • Async gRPC Servers to do the matrix multiplication and addition
    • Async gRPC Clients

Setup with Docker

  • Run docker-compose build to build images
  • Running docker-compose up should run 1 REST container and 3 gRPC server containers.
  • Visit http://0.0.0.0:8010/docs to access the API

Setup without Docker

  • Install the dependencies
    • pip install -r gRPC/requirements.txt
    • pip install -r REST/requirements.txt
  • Run 3 gRPC Servers on different ports
    • Sample: python async_grpcServer.py --port=8000
  • Modify the client listeners in REST/async_grpcClient.py file to point to the running gRPC servers.
  • Run FastAPI app
    • uvicorn async_app:app --port=8010
  • Visit http://0.0.0.0:8010/docs to access the API