摘要：
Operating systems are built and designed around two driving forces: the capabilities of hardware, and the demands of software. Yet traditional (read: old) operating systems and programming models have inertia, resulting in interfaces for new hardware following the designs of existing interfaces. As a result, programmers are limited in their ability to express the important parts of their programs due to the layers of compatibility and overhead thrust upon them, despite their persistent demands for higher throughput and lower latency. Operating system abstractions must evolve into the modern day. Merely relying on decades old abstractions and incremental change will relegate novel hardware of the last decade to a fate of access via interfaces designed for tape and spinning rust. We stand before an opportunity to study how a confluence of trends may shift programming models away from a traditional, process-centric view point towards a data-centric one, in which data is the primary citizen of the system. This opportunity arises from trends in hardware that directly impact how we view the data access path and the responsibilities ofthe operating system and the kernel. The increasing speed of interconnect technologies draws computing nodes closer together in latency space, increasing the efficiency and useability of shared memory. Persistence, traditionally trapped low in the memory hierarchy, is leaking upward, as access speeds for persistent devices increase (sidenote: this includes new technologies like byte-addressible non-volatile memory DIMMs, but also improvements in SSD performance and interfaces). As a result, the overhead of the traditional kernel-driven data access path begins to dominate the cost of accessing persistent data. Finally, the increasing heterogeneity and disaggregation of compute and memory devices demands increased data and compute mobility, as software demands continued scalability, distribution, and raw speed. This dissertation presents a new,
