Near-Data Data Transformation

BU faculty members Manos Athanassoulis and Renato Mancuso will work with Red Hat researchers Uli Drepper and Ahmed Sanaullah to create a hardware-software co-design paradigm for data systems that implements near-memory processing. The approach has the potential to revolutionize data management by bridging the gap of analytical and transactional processing. This paradigm addresses the performance bottleneck caused by memory bandwidth and will allow both cloud and edge systems to efficiently handle mixed transactional and analytics data-intensive workloads with a better trade-off between bandwidth and latency. “The proposed software-hardware co-design methodology will also improve the collective understanding of new design models and resource management strategies that are possible in systems with programmable memory hierarchies,” the team wrote.

Please see the arxiv version of our ongoing work.

This work has also received support (a gift) from Cisco

Looking ahead (details to be added)

  • Accepted paper for publication for EDBT 2023. Title of the paper: “Relational Memory: Native In-Memory Accesses on Rows and Columns”
  • Presentation accepted at DevConf 2022

Principal Investigator: Manos Athanassoulis

Co-PI: Renato Mancuso

Red Hat Collaborators: Uli Drepper and Ahmed Sanaullah

Project Poster

Link to full size poster