In order to simplify the node-wise scheduling algorithm of the alternating direction method of multipliers (NS-ADMM) decoding, approximate line segment projection algorithm (LSA) is adopted to perform the projection i...
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In order to simplify the node-wise scheduling algorithm of the alternating direction method of multipliers (NS-ADMM) decoding, approximate line segment projection algorithm (LSA) is adopted to perform the projection in the node-wise scheduling algorithm. Experimental results show that using approximate line segment projection instead of precise projection in node-wise scheduling algorithm will yield a poor frame error rate (FER) performance. To solve this problem, dynamic scheduling strategy that selects the message-passing schedule according to the convergence status of the check node is proposed. Simulation results demonstrate that the modified node-wise scheduling algorithm based on line segment projection outperforms existing decoding algorithms in terms of FER performance and convergence speed, while it has good error correction performance with a lower computational complexity.
In this paper, a novel dynamic priority scheduling algorithm for ROS 2 systems is proposed. The algorithm is based on determining deadlines of callbacks by taking the buffer size and update rates of channels into...
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The adoption of heterogeneous multicore architectures into deadline-constrained embedded systems has various benefits in terms of schedulability and energy-efficiency. Existing energy-efficient algorithms, in this dom...
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The adoption of heterogeneous multicore architectures into deadline-constrained embedded systems has various benefits in terms of schedulability and energy-efficiency. Existing energy-efficient algorithms, in this domain, allocate tasks to their energy-favorable core-types while using dynamic voltage and frequency scaling to reduce energy consumption. However, the practicality of such algorithms is limited due to the underlying assumptions made to simplify the analysis. This article paves the way for more practical approaches to minimize the energy consumption on heterogeneous multicores. Specifically, we investigate the nonlinear impacts that core-frequency and cache-partitioning have on task-executions in a heterogeneous multicore environment. In doing so, we propose an algorithm that exploits this relationship to effectively allocate tasks to specific cores and core-types, and determine the number of cache-partitions for each core. Extensive simulations using real-world benchmarks show the proficiency of our approach by achieving an average and maximum energy savings of 14.9 and 20.4 percent, respectively for core-level energy consumption, and 20.2 and 60.4 percent, respectively for system-level energy consumption.
ESBMC v7.7 improves the verification of concurrent C programs by incorporating techniques such as dynamic thread scheduling, incremental SMT solving, and partial order reduction (POR). These improvements enhance the t...
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The rapid development of cloud-native architecture has promoted the widespread application of container technology, but the optimization problems in container scheduling and resource management still face many challen...
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The conventional dynamic task scheduling method of multi-level distributed query engine mainly uses DAG (Directed Acyclic Graph) to generate task allocation scheduler, which is vulnerable to changes in task workflow, ...
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Fog computing stands as a recent and significant technological advancement in the realm of computing technologies, addressing several limitations inherent in cloud computing and yielding diverse optimizations. As the ...
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In 2013, Cuturi [9] introduced the Sinkhorn algorithm for matrix scaling as a method to compute solutions to regularized optimal transport problems. In this paper, aiming at a better convergence rate for a high accura...
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ISBN:
(纸本)9781611977714
In 2013, Cuturi [9] introduced the Sinkhorn algorithm for matrix scaling as a method to compute solutions to regularized optimal transport problems. In this paper, aiming at a better convergence rate for a high accuracy solution, we work on understanding the Sinkhorn algorithm under regularization scheduling, and thus modify it with a mechanism that adaptively doubles the regularization parameter eta periodically. We prove that such modified version of Sinkhorn has an exponential convergence rate as iteration complexity depending on log(1/epsilon) instead of epsilon(-O(1)) from previous analyses [1, 9] in the optimal transport problems with integral supply and demand. Furthermore, with cost and capacity scaling procedures, the general optimal transport problem can be solved with a logarithmic dependence on 1/epsilon as well.
With the widespread adoption of 5G and Internet of Things (IoT) technologies, the low latency provided by edge computing has great importance for real-time processing. However, managing numerous simultaneous service r...
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In cloud computing, task scheduling has a direct influence on service quality. Task scheduling means allocating tasks to available resources based on user specifications. This NP-hard problem seeks to develop an optim...
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