(Presenting on Wed. 11/28/18) With the pursuit of better performance under strict physical constraints, there is an increasing need for deploying applications to heterogeneous compute architectures with accelerators. Among these accelerators, intelligent memory and storage (IMS) architectures are proposed to provide an environment where the computation can be as close as possible to the memory cells. This kind of architecture can potentially greatly increase parallelism and energy efficiency, which enables us to run data-intensive applications.
This project aims at developing an intuitive programming model that provides high-level abstractions for programming heterogeneous accelerator architectures, including FPGAs and IMS accelerators.
