Presentation
HPC on a Reconfigurable Substrate with Machine Learning Support
SessionTenth International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC '24)
DescriptionStatic RAM FPGAs with their reconfigurability yields options to accomplish instruction set metamorphism or dynamic creation of accelerators/coprocessors as needed. In addition, the abundance of matrix multiplications in many HPC problems also gives the possibility to utilize Machine Learning (ML) support on FPGAs to achieve customized dynamic reconfiguration. Many HPC problems can be solved by Processing-in-Memory, and hence BlockRAMs enhanced with computing can be utilized to accelerate HPC applications. In this talk, I will describe some emerging avenues for reconfigurable HPC considering ML Support in FPGAs.