Authors:
Enrico Zanardo
Addresses:
Department of Computer Science and Engineering, Universitas Mercatorum, Rome, Italy. enrico.zanardo@studenti.unimercatorum.it
This article introduces Chronostamp, a versatile data-flow execution engine designed to simplify distributed programming while enabling advanced computational capabilities. Unlike traditional execution engines, Chronostamp supports data-dependent control-flow decisions, allowing it to handle complex tasks that involve iterative and recursive algorithms. This feature makes Chronostamp particularly well-suited for applications requiring dynamic data processing and flexible control structures. Deployed on a cloud computing platform, Chronostamp demonstrates scalable performance across iterative and non-iterative workloads. Its ability to effectively manage complex computations and dynamically adjust to data dependencies sets it apart from conventional execution engines. By abstracting the complexity of distributed programming, Chronostamp empowers developers to focus on algorithm design rather than low-level system details. Overall, Chronostamp offers a powerful tool for tackling intricate data processing tasks, enhancing the efficiency of big data analytics and iterative problem-solving applications. Its scalable performance and advanced control-flow capabilities make it a valuable asset for cloud-based data processing environments, highlighting its potential to transform the distributed computing landscape.
Keywords: Parallel Programming; Distributed Execution Engine; Distributed Data-flow; Chronostamp Run-time System; Load Balancing Mechanism; Fault Tolerance; Image Processing.
Received on: 12/12/2023, Revised on: 01/02/2024, Accepted on: 07/04/2024, Published on: 07/06/2024
AVE Trends in Intelligent Computing Systems, 2024 Vol. 1 No. 2, Pages: 106-115