Dataflow Optimization

Definition ∞ Dataflow Optimization involves structuring the movement and processing of information within a system to maximize efficiency and throughput. In computing, this aims to reduce latency and enhance resource utilization. It focuses on minimizing redundant operations and streamlining data paths.
Context ∞ In blockchain and digital asset systems, dataflow optimization is crucial for improving transaction speeds and network scalability. Efficient data handling can significantly reduce the computational burden on nodes, allowing for more transactions per second. This directly impacts user experience and the practical applicability of decentralized applications, making it a frequent topic in discussions about blockchain upgrades.