Wed 7 Nov 2018 11:15 - 11:37 at Studio 2 - Parallelism and Performance Chair(s): Arjun Guha

To leverage the benefits of modern hardware, dynamic languages must support parallelism, and parallelism requires a virtual machine (VM) capable of parallel execution — a parallel VM. However, unrestricted concurrency and the dynamism of dynamic languages pose great challenges to the implementation of parallel VMs. In a dynamic language, a program changing itself is part of the language model. To help the VM, languages often choose memory models (MM) that weaken consistency guarantees. With lesser guarantees, local program state cannot be affected by every concurrent state change. And less interference allows a VM to make local assumptions about the program state which are not immediately violated. These local assumptions are essential for a VM’s just-in-time compiler for delivering state-of-the-art VM performance.

Unfortunately, some dynamic languages employ MMs that give exceedingly strong consistency guarantees and thereby hinder the development of parallel VMs. Such is the case in particular for languages that depend on a global interpreter lock, which mandates a MM with sequential consistency and instruction atomicity.

In this paper, we reflect on a first implementation of the Parallel RPython execution model, which facilitates the development of parallel VMs by decoupling language semantics from the synchronization mechanism used within the VM. The implementation addresses the challenges imposed by strong MMs through strict isolation of concurrent computations. This isolation builds on transactional parallel worlds, which are implemented with a novel combination of software techniques and the capabilities of modern hardware.

We evaluate a set of parallel Python programs on a parallel VM that relies on Parallel RPython’s implementation. Compared with a serial baseline VM that relies on a global interpreter lock, the parallel VM achieves speedups of up to 7.5× on 8 CPU cores. The evaluation shows that our realization of Parallel RPython meets the challenges of dynamic languages, and that it can serve as a solid foundation for the construction of parallel dynamic language VMs.

Wed 7 Nov
Times are displayed in time zone: Guadalajara, Mexico City, Monterrey change

10:30 - 12:00: Parallelism and PerformanceOOPSLA at Studio 2
Chair(s): Arjun GuhaUniversity of Massachusetts Amherst
10:30 - 10:52
Every Data Structure Deserves Lock-Free Memory Reclamation
Nachshon CohenEPFL, Switzerland
10:52 - 11:15
Parallelization of Dynamic Languages: Synchronizing Built-in Collections
Benoit DalozeJKU Linz, Austria, Arie TalTechnion, Stefan MarrUniversity of Kent, Hanspeter MössenböckJKU Linz, Austria, Erez PetrankTechnion
11:15 - 11:37
Virtual Machine Design for Parallel Dynamic Programming Languages
Remigius MeierETH Zurich, Switzerland, Armin, Switzerland, Thomas GrossETH Zurich
11:37 - 12:00
goSLP: Globally Optimized Superword Level Parallelism Framework