Wed 7 Nov 2018 10:52 - 11:15 at Studio 2 - Parallelism and Performance Chair(s): Arjun Guha

Dynamic programming languages such as Python and Ruby are widely used, and much effort is spent on making them efficient. One substantial research effort in this direction is the enabling of parallel code execution. While there has been significant progress, making dynamic collections efficient, scalable, and thread-safe is an open issue. Typical programs in dynamic languages use few but versatile collection types. Such collections are an important ingredient of dynamic environments, but are difficult to make safe, efficient, and scalable.

In this paper, we propose an approach for efficient and concurrent collections by gradually increasing synchronization levels according to the dynamic needs of each collection instance. Collections reachable only by a single thread have no synchronization, arrays accessed in bounds have minimal synchronization, and for the general case, we adopt the Layout Lock paradigm and extend its design with a lightweight version that fits the setting of dynamic languages. We apply our approach to Ruby’s Array and Hash collections. Our experiments show that our approach has no overhead on single-threaded benchmarks, scales linearly for Array and Hash accesses, achieves the same scalability as Fortran and Java for classic parallel algorithms, and scales better than other Ruby implementations on Ruby workloads.

Wed 7 Nov

splash-2018-OOPSLA
10:30 - 12:00: OOPSLA - Parallelism and Performance at Studio 2
Chair(s): Arjun GuhaUniversity of Massachusetts Amherst
splash-2018-OOPSLA10:30 - 10:52
Talk
Nachshon CohenEPFL, Switzerland
splash-2018-OOPSLA10:52 - 11:15
Talk
Benoit DalozeJKU Linz, Austria, Arie TalTechnion, Stefan MarrUniversity of Kent, Hanspeter MössenböckJKU Linz, Austria, Erez PetrankTechnion
Pre-print
splash-2018-OOPSLA11:15 - 11:37
Talk
Remigius MeierETH Zurich, Switzerland, Armin RigoPyPy.org, Switzerland, Thomas GrossETH Zurich
splash-2018-OOPSLA11:37 - 12:00
Talk