Enforcing Deadlines for Skeleton-based Parallel Programming

High throughput applications with real-time guarantees are increasingly relevant. For these applications, parallelism must be exposed to meet deadlines. Directed Acyclic Graphs (DAGs) are a popular and very general application model that can capture any possible interaction among threads. However, w...

Full description

Saved in:
Bibliographic Details
Published in:Proceedings / IEEE Real-Time and Embedded Technology and Applications Symposium pp. 188 - 199
Main Authors: Metzger, Paul, Cole, Murray, Fensch, Christian, Aldinucci, Marco, Bini, Enrico
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2020
Subjects:
Analytical models
Directed acyclic graph
Microcontrollers
Parallel processing
Parallel programming
Skeleton
Throughput
ISSN:2642-7346
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:High throughput applications with real-time guarantees are increasingly relevant. For these applications, parallelism must be exposed to meet deadlines. Directed Acyclic Graphs (DAGs) are a popular and very general application model that can capture any possible interaction among threads. However, we argue that by constraining the application structure to a set of composable "skeletons", at the price of losing some generality w.r.t. DAGs, the following advantages are gained: (i) a finer model of the application enables tighter analysis, (ii) specialised scheduling policies are applicable, (iii) programming is simplified, (iv) specialised implementation techniques can be exploited transparently, and (v) the program can be automatically tuned to minimise resource usage while still meeting its hard deadlines. As a first step towards a set of real-time skeletons we conduct a case study with the job farm skeleton and the hard real-time XMOS xCore-200 microcontroller. We present an analytical framework for job farms that reduces the number of required cores by scheduling jobs in batches, while ensuring that deadlines are still met. Our experimental results demonstrate that batching reduces the minimum sustainable period by up to 22%, leading to a reduced number of required cores. The framework chooses the best parameters in 83% of cases and never selects parameters that cause deadline misses. Finally, we show that the overheads introduced by the skeleton abstraction layer are negligible.
ISSN:2642-7346
DOI:10.1109/RTAS48715.2020.000-7