Scalable Task Parallelism for NUMA: A Uniform Abstraction for Coordinated Scheduling and Memory Management

In Abstract

Scalable Task Parallelism for NUMA: A Uniform Abstraction for Coordinated Scheduling and Memory Management
An automatic run-time optimisation system has been developed that allows programmers to ignore non-uniformity in parallel computing systems without sacrificing performance.

The research was conducted by an international team of computer scientists led from the University of Manchester. The resulting system allows software engineers to harness the ever-increasing power of contemporary computing systems without being exposed to their complexity. The system is automatic, application-independent, performance-portable across machines, and adapts seamlessly to dynamic changes.

While computing devices have become faster and more energy-efficient every year, this capability is often not translated into faster and more efficient applications for users. This is due to the difficulty of writing programs that can cope with the significant static and dynamic non-uniformity in modern computing systems. The optimization strategy uses semantic program information, gathered during compilation, to make precise scheduling and memory placement decisions at run time. This dynamic approach allows the preservation of a uniform hardware abstraction for programmers, leaving the work of managing non-uniformity to an automated run-time system.

It is anticipated that this research will influence the key trade-offs that determine how computing systems are designed and, eventually, lead to significant changes in the way software is deployed and optimised in future computing systems.

Click here to read the full article - DOI: 10.1145/2967938.2967946