NPM-BUNDLE: Non-Preemptive Multitask Scheduling for Jobs with BUNDLE-Based Thread-Level Scheduling

Tessler, Corey; Fisher, Nathan

doi:10.4230/lipics.ecrts.2019.15

Cited by 1 publication

(3 citation statements)

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“…A positive perspective of caches is taken by BUNDLE [54][55][56] for multi-threaded tasks running on a single processor. This positive perspective is reflected in the WCET of a task which includes the inter-thread cache benefit: the speed-up one thread experiences by another placing values in the cache.…”

Section: Related Workmentioning

confidence: 99%

“…Tasks in the BUNDLE [54][55][56] model are represented by a tuple τ i = (p i , d i , c i (η i ), η i , o i ). A task has the familiar minimum inter-arrival time p i and relative deadline d i .…”

Section: A Bundlementioning

confidence: 99%

“…In the setting of uniprocessor multi-threaded task systems, the BUNDLE-based approaches [54][55][56] (referred to as BUNDLE throughout the rest of this work) treat cache memory positively, creating a benefit to schedulability. BUNDLE restricts the execution of the multiple threads of task on a single processor in a cache cognizant manner.…”

Section: Introductionmentioning

confidence: 99%

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Bringing Inter-Thread Cache Benefits to Federated Scheduling -- Extended Results & Technical Report

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Multiprocessor scheduling of hard real-time tasks modeled by directed acyclic graphs (DAGs) exploits the inherent parallelism presented by the model. For DAG tasks, a node represents a request to execute an object on one of the available processors. In one DAG task, there may be multiple execution requests for one object, each represented by a distinct node. These distinct execution requests offer an opportunity to reduce their combined cache overhead through coordinated scheduling of objects as threads within a parallel task. The goal of this work is to realize this opportunity by incorporating the cacheaware BUNDLE-scheduling algorithm into federated scheduling of sporadic DAG task sets. This is the first work to incorporate instruction cache sharing into federated scheduling. The result is a modification of the DAG model named the DAG with objects and threads (DAG-OT). Under the DAG-OT model, descriptions of nodes explicitly include their underlying executable object and number of threads. When possible, nodes assigned the same executable object are collapsed into a single node; joining their threads when BUNDLEscheduled. Compared to the DAG model, the DAG-OT model with cache-aware scheduling reduces the number of cores allocated to individual tasks by approximately 20 percent in the synthetic evaluation and up to 50 percent on a novel parallel computing platform implementation. By reducing the number of allocated cores, the DAG-OT model is able to schedule a subset of previously infeasible task sets.

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Section: Related Workmentioning

confidence: 99%

Section: A Bundlementioning

confidence: 99%