LVars: monotonic update for deterministic parallel programming

LVars are one outcome of Lindsey Kuper's ongoing PhD work at Indiana University. They generalize existing models for deterministic parallelism by considering a general framework of monotonic read and write operations. They were briefly mentioned on LtU before (along with the strongly related work on Bloom in the distributed systems community), and were recently presented in two distinct and complementary articles.

The first article describes the basic building blocks and ideas of LVars:

LVars: Lattice-Based Data Structures for Deterministic Parallelism
Lindsey Kuper, Ryan R. Newton

Programs written using a deterministic-by-construction model of parallel computation are guaranteed to always produce the same observable results, offering programmers freedom from subtle, hard-to-reproduce nondeterministic bugs that are the scourge of parallel software. We present LVars, a new model for deterministic- by-construction parallel programming that generalizes existing single-assignment models to allow multiple assignments that are monotonically increasing with respect to a user-specified lattice.

LVars ensure determinism by allowing only monotonic writes and "threshold" reads that block until a lower bound is reached. We give a proof of determinism and a prototype implementation for a language with LVars and describe how to extend the LVars model to support a limited form of nondeterminism that admits failures but never wrong answers

The second relaxes the original model by introducing failure, which widens its applicability:

Freeze After Writing: Quasi-Deterministic Parallel Programming with LVars
Lindsey Kuper, Aaron Turon, Neelakantan Krishnaswami, Ryan R. Newton

Deterministic-by-construction parallel programming models offer programmers the promise of freedom from subtle, hard-to-reproduce nondeterministic bugs in parallel code. A principled approach to deterministic-by-construction parallel programming with shared state is offered by LVars: shared memory locations whose semantics are defined in terms of a user-specified lattice. Writes to an LVar take the least upper bound of the old and new values with respect to the lattice, while reads from an LVar can observe only that its contents have crossed a specified threshold in the lattice. Although it guarantees determinism, this interface is quite limited.

We extend LVars in two ways. First, we add the ability to “freeze” and then read the contents of an LVar directly. Second, we add the ability to attach callback functions to an LVar, allowing events to be triggered by writes to it. Together, callbacks and freezing enable an expressive and useful style of parallel programming. We prove that in a language where communication takes place through freezable LVars, programs are at worst quasi-deterministic: on every run, they either produce the same answer or raise an error. We demonstrate the viability of our approach by implementing a library for Haskell supporting a variety of LVar-based data structures, together with two case studies that illustrate the programming model and yield promising parallel speedup.

Something I personally found surprising and impressive about LVars is that, while I was initially interested in the very formal aspects of providing a theoretical framework for deterministic concurrency, it very quickly produced a practical library that people can use to write parallel program -- and competitive with existing high-performance approaches. As described in a recent blog post, a Haskell library is available on Hackage -- but surely LVars-inspired libraries could make sense in a lot of other languages as well.

Alexander Bumstead learns the Lambda Calculus

See the daily Blondie comic strip for October 3, 2013.