As part of the upcoming H2020 E2Data project, we are interested in exploiting heterogeneous hardware resources on Big Data stacks. Our main interest is in sharing resources for researching and developing novel tool and components for dynamic acceleration of data analytics.
We expect to contribute knowledge and insights regarding dynamic compilation and reconfiguration of data analytics code executed on top of managed runtime environments. E2Data proposes an end-to-end solution for Big Data deployments that fully exploits and advances the state-of-the-art in infrastructure services by delivering significant performance increase with much less cloud resources. E2Data provides a new Big Data software paradigm of achieving the maximum resource utilisation for heterogeneous cloud deployments without affecting current Big Data programming norms (i.e. no code changes in the original source). This will be achieved by co-designing the Big Data stack and applications with novel compiler and run-time components for dynamic and intelligent acceleration based on each individual scenario.