Collaborative Research: PPoSS: Planning: Fixpoint: an operating system and architecture for data-centric computing

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Computer operating systems run programs that read input data and produce output data. However, today's operating systems generally don't keep track of enough information to make sure that the process of generating a given piece of data can be reproduced, especially when the program that produced it may have considered input that came over the network, from a mutable file on disk, or from a non-deterministic phenomenon such as thread scheduling. This project will design a new kind of operating system, called Fixpoint, that explicitly represents and names computations on data: each invocation of a program, in terms of its minimal data-dependencies, in a reproducible content-addressed manner. If successful, the project will have a significant impact on how computer systems are used every day. By making all computation reproducible by default and trivially shareable, Fixpoint can improve scientific reproducibility and as a consequence increase the public's confidence in scientific results. The hypothesis of this project is that by changing the way software is represented, substantial benefits can be unlocked in the areas of scalability, security, efficiency, performance, and reproducibility. Fixpoint's operating-system-visible dataflow will give it an ability to take advantage of massive transient parallelism, which means that parallel tasks that effectively require batch-processing today -- submitting jobs to servers and waiting hours -- will become near real-time. This will change the kinds of operations that people expect to do interactively at a computer. Errors discovered in data, even after the fact, can be backed out of computations that depend on them, similar to recalculating a spreadsheet today.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.