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Deep convolutional neural networks (CNNs) are widely adopted in intelligent systems with unprecedented accuracy but at the cost of a substantial amount of data movement. Although recent development in processing-in-memory (PIM) architecture seeks to minimize data movement by computing the data at the dedicated nonvolatile device, how to jointly explore the computation capability of PIM and utilize...
In this paper, we consider an energy harvesting multiple access channel (MAC) where the transmitters are powered by energy harvested from the ambient environment. We assume that the energy harvesting processes at the transmitters can be modeled as independent Bernoulli processes with parameters λis, and the channel states between the transmitters and the receiver are independent Bernoulli processes...
In this paper, we consider a collaborative sensing scenario where sensing nodes are powered by energy harvested from environment. We assume that in each time slot, the utility generated by sensing nodes is a function of the number of the active sensing nodes in that slot. Under the energy causality constraint at every sensor, our objective is to develop a collaborative sensing scheduling for the sensors...
This paper develops a model for scheduling large-scale hydrothermal power systems based on the Mixed Integer linear Programming (MILP) technique. The advantage of this model is that the schedules can make coordinated decision for hydro and thermal units, take into full account the hydro unit constraints in achieving overall economy of power system operation. The planning problem is not decomposed...
This paper presents a formal method for equivalence checking between the descriptions before and after scheduling in high-level synthesis (HLS). Both descriptions are represented by finite state machine with datapaths (FSMDs) and are then characterized through finite sets of paths. The main target of our proposed method is to verify scheduling employing code transformations-such as speculation and...
Stochastic search algorithms are often robust, scalable problem solvers. In this paper, we carefully study the Iterative Sampling(IS), Heuristic-Biased Stochastic Sampling(HBSS) and Value-Biased Stochastic Sampling(VBSS) algorithm, and present an approach for enhancing such multi-start algorithms. This paper shows that given some heuristic information about the search start point, these algorithms...
Aiming at the problems that there is a big difference between the parallel total time of operations and real parallel time in processing and assembly integrated scheduling of dynamic complex product to confirm increasable bottleneck device, and an algorithm which can confirm the increasable bottleneck device in dynamic integrated scheduling based on static parallel time is presented. Firstly, a processing...
We consider the transmission completion time minimization problem in a single-user energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modelled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the transmission completion time is...
At present, scheduling research with batching machines mainly solves scheduling problem without constraint among operations. There is no effective scheduling method for complex product with batching machines. To that end, a new algorithm is proposed to solve dynamic scheduling problem for complex product with batching machines. And the maximum lot-size of the batching machines is two. First, based...
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