Improved Task and Resource Partitioning Under the Resource-Oriented Partitioned Scheduling

Chen, Ze-Wei; Lei, Hang; Yang, Maolin; Liao, Yong; Yu, Jiali

doi:10.1007/s11390-019-1945-5

Cited by 9 publications

(6 citation statements)

References 34 publications

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“…A heuristic for resource-oriented task partitioning in multicores is presented in [41]. Other partitioning strategies are proposed in [26]. All these works, however, target only homogeneous multicores.…”

Section: Related Workmentioning

confidence: 99%

Optimized Partitioning and Priority Assignment of Real-Time Applications on Heterogeneous Platforms with Hardware Acceleration

Casini,

Pazzaglia,

Biondi

et al. 2022

Preprint

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Hardware accelerators, such as those based on GPUs and FPGAs, offer an excellent opportunity to efficiently parallelize functionalities. Recently, modern embedded platforms started being equipped with such accelerators, resulting in a compelling choice for emerging, highly computational intensive workloads, like those required by next-generation autonomous driving systems. Alongside the need for computational efficiency, such workloads are commonly characterized by real-time requirements, which need to be satisfied to guarantee the safe and correct behavior of the system. To this end, this paper proposes a holistic framework to help designers partition real-time applications on heterogeneous platforms with hardware accelerators. The proposed model is inspired by a realistic setup of an advanced driving assistance system presented in the WATERS 2019 Challenge by Bosch, further generalized to encompass a broader range of heterogeneous architectures. The resulting analysis is linearized and used to encode an optimization problem that jointly (i) guarantees timing constraints, (ii) finds a suitable task-to-core mapping, (iii) assigns a priority to each task, and (iv) selects which computations to accelerate, seeking for the most convenient trade-off between the smaller worst-case execution time provided by accelerators and synchronization and queuing delays.

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Section: Related Workmentioning

confidence: 99%

Optimized Partitioning and Priority Assignment of Real-Time Applications on Heterogeneous Platforms with Hardware Acceleration

Casini,

Pazzaglia,

Biondi

et al. 2022

Preprint

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“…The latter seeks to partition a graph into even-sized components while minimizing the number of edges. Figure 1 summarizes other problems that can be modeled as Balanced Partition, including: People Assignment [34], Routing [31], [35]- [38], Task Allocation [39], [40], File Placement [41], [42] and Scheduling [43]- [45]. We briefly describe them in the following lines.…”

Section: A Balanced Partition (Bp)mentioning

confidence: 99%

Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites

et al. 2021

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Combinatorial optimization problems (COPs) are paramount for real-life problems with discrete variables. Even though the number of combinations is finite, some problems exhibit exponential growth, rendering exact approaches unfeasible. So, approximate methods, such as heuristics, are customary for making fast decisions. Despite their small computational cost, each heuristic specializes in specific kinds of problems. Hence, other approaches have appeared for merging their strengths. One of these approaches is commonly known as selection hyper-heuristics. However, a trained hyper-heuristic usually carries the following problem: it provides scarce information about its sensitivity. This makes it more difficult to estimate the effect of changing a parameter. Illumination algorithms seek to improve this issue by focusing on exploration rather than on exploitation while preserving information about the best solutions with different criteria. Still, literature falls short when merging both approaches, representing a knowledge gap. Therefore, in this work, we test the feasibility of using an illumination algorithm, the MAP-Elites (ME), for tuning a sequence-based selection hyper-heuristic model for Balanced Partition problems. We choose ME since it has been successfully applied to a different COP, and by linking it with hyper-heuristics, we may exploit upon its benefits. So, we may achieve a hyper-heuristic that represents the best combination of heuristics. Simultaneously, we can gain information about the expected performance of diverse hyperheuristics, e.g., those that begin with a different heuristic. Our approach operates by creating a multidimensional map, where each design variable represents the application of a given heuristic. Afterward, ME generates mutated sequences and tests them to determine if they represent a better-performing solution. To test our approach, we consider 1500 instances that include easy and hard instances, analyzed under different scenarios. We also include limit instances that are neither easy nor hard. Our resulting data supports the feasibility of the proposed approach. We show that this kind of hyper-heuristic can perform toe-to-toe with a synthetic oracle. Besides, under some conditions, the former may even outperform the latter. This represents an outstanding result, since such an oracle can only be obtained by a brute-force approach, and because it demonstrates that merging both approaches (ME and hyper-heuristics) is a path worth pursuing. We also present how each parameter affects the model performance, concluding that some parameters can be critical while others are virtually irrelevant. This is also a relevant result, since it serves as the groundwork for future works so that they can focus on exploiting the most relevant parameters.

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“…From an analytical point of view-i.e., for the purpose of schedulability and blocking analysis-the first two interpretations are equivalent, that is, identical analysis problems must be solved and, ignoring overheads, identical bounds are obtained, regardless of how the protocol is actually implemented. The third approach provides some additional flexibility [189,195] and has recently been exploited to enable modern analyses and heuristics [70,76,114,115,198].…”

Section: Centralized Execution Of Critical Sectionsmentioning

confidence: 99%

“…Over the years, many results pertaining to the task and resource mapping problems as well as related optimization problems have appeared [13,34,70,76,87,88,99,100,101,111,112,115,134,149,152,154,168,180,189,195,198,208]. Particularly well-known is Lakshmanan et al's task-set partitioning heuristic for use with the MPCP [123].…”

Section: Further Research Directionsmentioning

confidence: 99%

“…Alternative heuristics and strategies have been proposed by (among others) Nemati et al [154], Wieder and Brandenburg [208], and Al-bayati et al [13]. Most recently, Dong et al [76] presented a detailed study of several task-and resource-assignment heuristics following a resource-centric schedulability analysis approach [114,115] in the context of a semaphore protocol with centralized critical sections, and Chen et al [70] presented an ILP-based partitioning solution for the same workload and platform model. Techniques for scheduling task graphs with precedence constraints and end-to-end deadlines in distributed systems [189,195] are particularly relevant in the context of the DPCP and its related task and resource mapping problems.…”

Section: Further Research Directionsmentioning

confidence: 99%

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Multiprocessor Real-Time Locking Protocols: A Systematic Review

Brandenburg

2019

Preprint

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We systematically survey the literature on analytically sound multiprocessor real-time locking protocols from 1988 until 2018, covering the following topics:• progress mechanisms that prevent the lock-holder preemption problem (Section 3),• spin-lock protocols (Section 4),• binary semaphore protocols (Sections 5 and 6),• independence-preserving (or fully preemptive) locking protocols (Section 7),• reader-writer and k-exclusion synchronization (Section 8),• support for nested critical sections (Section 9), and • implementation and system-integration aspects (Section 10).A special focus is placed on the suspension-oblivious and suspension-aware analysis approaches for semaphore protocols, their respective notions of priority inversion, optimality criteria, lower bounds on maximum priority-inversion blocking, and matching asymptotically optimal locking protocols.

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Improved Task and Resource Partitioning Under the Resource-Oriented Partitioned Scheduling

Cited by 9 publications

References 34 publications

Optimized Partitioning and Priority Assignment of Real-Time Applications on Heterogeneous Platforms with Hardware Acceleration

Optimized Partitioning and Priority Assignment of Real-Time Applications on Heterogeneous Platforms with Hardware Acceleration

Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites

Multiprocessor Real-Time Locking Protocols: A Systematic Review

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