Incremental computation with names

Abstract

Over the past thirty years, there has been significant progress in developing general-purpose, language-based approaches to incremental computation, which aims to efficiently update the result of a computation when an input is changed. A key design challenge in such approaches is how to provide efficient incremental support for a broad range of programs. In this paper, we argue that first-class names are a critical linguistic feature for efficient incremental computation. Names identify computations to be reused across differing runs of a program, and making them first class gives programmers a high level of control over reuse. We demonstrate the benefits of names by presenting NOMI-NAL ADAPTON, an ML-like language for incremental computation with names. We describe how to use NOMINAL ADAPTON to efficiently incrementalize several standard programming patterns-including maps, folds, and unfoldsand show how to build efficient, incremental probabilistic trees and tries. Since NOMINAL ADAPTON's implementation is subtle, we formalize it as a core calculus and prove it is from-scratch consistent, meaning it always produces the same answer as simply re-running the computation. Finally, we demonstrate that NOMINAL ADAPTON can provide large speedups over both from-scratch computation and ADAPTON, a previous state-of-the-art incremental computation system.

A survey of state management in big data processing systems

“…At the calculus level, researchers [17,34,47] focus on incremental state computation using algebra. Cai et al [17] introduce a new mathematical theory (i.e., the theory of changes and derivatives) for incremental computation.…”

“…Cai et al [17] introduce a new mathematical theory (i.e., the theory of changes and derivatives) for incremental computation. Hammer et al [47] use first-class names as the essential linguistic characteristic for efficient incremental computation. Fegaras [34] uses monoid homomorphisms as the underlying mechanism to propose an algebra for distributed computing.…”

FRP IoT modules as a Scala DSL

“…The second version provides safe access to local mutable state, something for which we do not have an alternative. Given the similarites between the two approaches a logical step for future work seems to incorporate the typeclass-based framework for incremental computing into the incremental behavior API which could give us alternative definitions such as: As a final note, Several SAC papers [2,9] refer to FRP and point out opportunities to combine the two, for example, [2] says "Although FRP research remained largely orthogonal to incremental computation, it may benefit from incremental computation, because computations performed at consecutive time steps can be similar.". Incremental behaviors may be a stepping stone towards a better integration of incremental computations in FRP.…”

A vision for online verification-validation

“…This approach is commonly taken by past work on incremental computation [7,8,17,24,25,33,34,34], however, it is brittle and overly sensitive to small changes, since they alter the identity of the whole recursive structure. Recent work addresses this shortcoming by introducing unique names that are special to incremental computing [26]. This naming mechanism can overcome the challenges outlined above for chk_stk, since the presence of names isolates changed components of the store typing, stack and local environments.…”