Abstract

Reproducibility is important in computing, whether reproducing bug reports or scientific results. After obvious sources of irreproducibility are addressed by containerization and hermetic build systems, the fundamental remaining challenge is preventing unintended nondeterminism due to parallelism and concurrency.

In this talk I present languages and libraries that provide strict deterministic parallelism by construction. Starting with a foundation that disallows writable shared memory between parallel computations, we add support for structured communication patterns that preserve the determinism guarantee, irrespective of the underlying architecture, thread count, and nondeterministic scheduling. Building an application with these patterns also clarifies its structure and supports formal reasoning about effect composition.

While the constraint of determinism may seem harsh, in this talk I argue that the future is bright: we can already build programs mixing lock-free concurrent data structures, blocking data-flow, callbacks, and GPU -based data-parallelism, without ever compromising determinism or referential transparency.

Bio:

Ryan Newton received his Ph.D. in computer science from MIT in 2009, advised by Arvind and Samuel Madden. His thesis introduced techniques for efficiently distributing a single logical program over a sensor network. From 2009 through 2011, Ryan was an engineer in the developer products division at Intel, where he worked on parallel programming tools, including Cilk and CnC. Since 2011, Ryan leads a group of programming languages researchers interested in increasing the safety and parallel performance of high-level, declarative programs.