A conventional data center that consists of monolithic-servers is confronted with limitations including lack of operational flexibility, low resource utilization, low maintainability, etc. Resource disaggregation is a promising solution to address the above issues. We propose a concept of disaggregated cloud data center architecture called Flow-in-Cloud (FiC) that enables an existing cluster computer system to expand an accelerator pool through a high-speed network. FlowOS-RM manages the entire pool resources, and deploys a user job on a dynamically constructed slice according to a user request. This slice consists of compute nodes and accelerators where each accelerator is attached to the corresponding compute node. This paper demonstrates the feasibility of FiC in a proof of concept experiment running a distributed deep learning application on the prototype system. The result successfully warrants the applicability of the proposed system.

Memory deduplication improves the utilization of physical memory by sharing identical blocks of data. Although memory deduplication is most effective when many virtual machines with same operating systems run on a CPU, cross-user memory deduplication is a covert channel and causes serious memory disclosure attack. It reveals the existence of an application or file on another virtual machine. The covert channel is a difference in write access time on deduplicated memory pages that are re-created by Copy-On-Write, but it has some interferences caused by execution environments. This paper indicates that the attack includes implementation issues caused by memory alignment, self-reflection between page cache and heap, and run-time modification (swap-out, anonymous pages, ASLR, preloading mechanism, and self-modification code). However, these problems are avoidable with some techniques. In our experience on KSM (kernel samepage merging) with the KVM virtual machine, the attack could detect the security level of attacked operating systems, find vulnerable applications, and confirm the status of attacked applications.