Distributed Computing

Concurrent processing refers to the execution of multiple processes simultaneously, improving efficiency and resource utilization in computing.

Distributed Computing involves multiple interconnected computers working together to solve complex tasks efficiently.

A Global Descriptor is a unique identifier for objects in a distributed computing environment.

A computing model where a master node delegates tasks to multiple worker nodes for efficient processing.

Message Passing Algorithm (MPA) is a technique for distributed computing where information is exchanged between nodes in a network.

Multi-Node Processing refers to the simultaneous execution of tasks across multiple computing nodes to enhance performance.

Multiprocessing is a computing technique that uses multiple processors to execute tasks simultaneously, enhancing performance and efficiency.

Parallel computing is a type of computation where many calculations are carried out simultaneously.

Ray is a distributed computing framework designed for building and running applications across clusters of computers.

Ray Serve is a scalable model serving library for machine learning models built on Ray.

Ray Tune is a scalable library for hyperparameter tuning in machine learning using Ray.

Secure Multi-Party Computation allows parties to jointly compute data while keeping their inputs private.

Tensor parallelism is a technique for distributing tensor computations across multiple processors to enhance performance.