BSF-skeleton

BSF-skeleton implements the Bulk Synchronous Farm (BSF) model to parallelize iterative numerical algorithms on cluster computing systems using a master/slave architecture.

Key Features:

• Scalability Estimation: Estimates the scalability of parallel algorithms prior to implementation to inform resource allocation and performance expectations.
• Data Representation: Employs a list-based representation for problem data to simplify data handling in parallel applications.
• Encapsulation of Parallelization Aspects: Encapsulates elements related to program parallelization to separate infrastructure concerns from algorithmic code.
• Error-Free Compilation: Provides error-free compilation at every stage of application development for iterative numerical algorithms.
• Programming Model Support: Supports C++ applications using the MPI (Message Passing Interface) library and also accommodates the OpenMP programming model.

Scientific Applications:

• Iterative numerical algorithms: Applied to high computational complexity tasks that use iterative numerical algorithms.
• Computational physics: Distributes computational workloads for simulations and numerical models in computational physics.
• Bioinformatics: Applies to large-scale bioinformatics computations requiring parallel processing across clusters.
• Large-scale simulations: Facilitates distribution of workloads across multiple cluster nodes for large-scale simulations.

Methodology:

Implements the Bulk Synchronous Farm (BSF) model with a master/slave architecture, uses a list-based data representation, supports MPI and OpenMP, and performs scalability estimation.