Collaborative Research: CNS Core: Medium: Movement of Computation and Data in Splitkernel-disaggregated, Data-intensive Systems

William Marsh Rice University, Houston TX

Investigators

Abstract

Resource disaggregation promises to change the way in which we design and operate cloud infrastructure. But despite its positive impact on the operation and cost-efficiency of data centers, disaggregation comes with overheads that arise from introducing a PCIe and network round trip for each access to remote memory, storage, or accelerators -- overheads that are particularly pronounced for data-intensive applications. The core research question that this proposal will answer is what the advent of disaggregation implies for the decades of architectural decisions made by the designers of data-intensive systems, and likewise, what OS-level primitives are required to adapt these systems to a disaggregated setting. To that end, this work proposes a co-design of disaggregated operating systems and middleware for data-intensive systems that achieves both high performance and ease of use, Data-intensive systems like the ones targeted by this work power much of today’s world, providing analytics for everything from business informatics to Internet search and healthcare. The proposed work will assist data center operators in transitioning their infrastructure to support resource disaggregation while minimizing performance overheads to applications written in common frameworks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.