A significant challenge we faced was managing a vast quantity of DFT calculations that demands careful monitoring of tasks, identifying and tracking errors, and rerunning them when necessary, which is a tedious but crucial process. Drawing inspiration from the GNU parallel tool , renowned for its user-friendly approach to executing multiple tasks concurrently, we have developed an in-house tool. This tool is designed for efficient and easy parallel execution and monitoring of multiple jobs. The cornerstone of our algorithm is its ability to maintain a task list in a lightweight database file supporting concurrent access by multiple processes. We employ SQLite3 for its lightweight nature, serverless architecture, cross-platform compatibility, and support with transactions for concurrent access by multiple processes.