Linear Algebra in ScyllaDB

ScyllaDB has been explored for its capabilities in distributed numerical calculations, particularly with large matrices, by using it as a distributed cluster that functions like RAM, enabling operations on matrices that wouldn't fit in traditional storage. The project focused on implementing a library for performing linear algebra computations using ScyllaDB, leveraging the Basic Linear Algebra Subprograms (BLAS) interface to facilitate integration with existing numerical codes. The researchers opted for a block-based representation of matrices, which allows efficient parallel computations by dividing tasks among multiple workers connected to ScyllaDB. This approach enhances scalability and concurrency, as demonstrated in benchmarks performed on AWS, which showed efficient matrix-matrix multiplication. The project also involved developing a modern C++ wrapper for the ScyllaDB driver to improve usability. The research, conducted with the University of Warsaw, resulted in a scalable solution for sparse computational algebra, with code available for public access on GitHub.