dispy

What is dispy?

dispy is a versatile Python framework that enables parallel execution of computations across multiple processors on a single machine, or distributed across a cluster or grid of interconnected systems. Designed to excel in the data parallel (SIMD) paradigm, dispy allows computations to be evaluated independently with large, diverse datasets, much like the approach used in Hadoop and MapReduce. The framework's key features include automatic distribution of computations and their dependencies, such as files, Python functions, classes, and modules, ensuring seamless execution. Additionally, dispy offers robust security measures, the ability to schedule computations on specific nodes as needed, and mechanisms for client-side and server-side fault recovery. The framework also supports the sharing of compute nodes, providing flexibility in resource utilization

Highlights

• Parallel execution across single machine or distributed cluster/grid
• Well-suited for data parallel (SIMD) computations with large datasets
• Automatic distribution of computations and dependencies (files, functions, classes, modules)
• Security features for safe computation execution
• Scheduling computations to specific nodes as required
• Client-side and server-side fault recovery
• Support for sharing of compute nodes