Synchronous Algorithm

Synchronous algorithms, which require all computational units to complete their tasks before proceeding, are facing challenges in distributed computing due to inherent inefficiencies caused by stragglers (slow devices) and communication delays. Current research focuses on developing asynchronous alternatives that allow for independent operation of units, improving efficiency in applications like federated learning and online change detection. These asynchronous methods aim to maintain accuracy while significantly reducing computation time, impacting fields ranging from AI model training to robotics and network security. The development of robust and provably convergent asynchronous algorithms is a key area of ongoing investigation.