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
2013
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
2014
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 “freezeâ€
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.
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