Vinay Devadas and Matthew Curtis-Maury, NetApp

Given continually increasing core counts, multiprocessor software scaling becomes critical. One set of applications that is especially difficult to parallelize efficiently are those that operate on hierarchical data. In such applications, correct execution relies on all threads coordinating their accesses within the hierarchy. At the same time, high performance execution requires that this coordination happen efficiently while maximizing parallelism.

New trends have been added to ATG’s research agenda.

New trends added include 5G/MEC, Cloud Native Databases, Quantum Computing, Data Containerization and Self-Managing Systems.

Hoda Maleki (University of Connecticut); Kyle Hogan (MIT); Reza Rahaeimehr (University of Connecticut); Ran Canetti, Mayank Varia, Jason Hennessey (Boston University and NetApp); Marten van Dijk (University of Connecticut); Haibin Zhang (UMBC)

Specifically, this work concentrates on the high-level struc-ture of OpenStack, leaving the further formalization and moredetailed analysis of specific OpenStack services to future work.Specifically, we formulate ideal functionalities that correspond tosome of the core OpenStack modules, and then proves securityof the overall OpenStack protocol given the ideal components.