To enhance the computational density and energy efficiency of on-chip neuromorphic hardware,this study introduces a novel network architecture for multi-task processing with in-memory optical computing.On-chip optical...To enhance the computational density and energy efficiency of on-chip neuromorphic hardware,this study introduces a novel network architecture for multi-task processing with in-memory optical computing.On-chip optical neural networks are celebrated for their capability to transduce a substantial volume of parameters into optical form while conducting passive computing,yet they encounter challenges in scalability and multitasking.Leveraging the principles of transfer learning,this approach involves embedding the majority of parameters into fixed optical components and a minority into adjustable electrical components.Furthermore,with deep regression algorithm in modeling physical propagation process,a compact optical neural network achieve to handle diverse tasks.In this work,two ultra-compact in-memory diffraction-based chips with integration of more than 60,000 parameters/mm^(2) were fabricated,employing deep neural network model and the hard parameter sharing algorithm,to perform multifaceted classification and regression tasks,respectively.The experimental results demonstrate that these chips achieve accuracies comparable to those of electrical networks while significantly reducing the power-intensive digital computation by 90%.Our work heralds strong potential for advancing in-memory optical computing frameworks and next generation of artificial intelligence platforms.展开更多
Stuttering is a common neurological deficit and its underlying cognitive mechanisms are a matter of debate, with evidence suggesting abnormal modulation between speech encoding and other cognitive components. Previous...Stuttering is a common neurological deficit and its underlying cognitive mechanisms are a matter of debate, with evidence suggesting abnormal modulation between speech encoding and other cognitive components. Previous studies have mainly used single task experiments to investigate the disturbance of language production. It is unclear whether there is abnormal interaction between the three language tasks （orthographic, phonological and semantic judgment） in stuttering patients. This study used dual tasks and manipulated the stimulus onset asynchrony （SOA） between tasks 1 and 2 and the nature of the second task, including orthographic, phonological, and semantic judgments. The results showed that the performance records of orthographic judgment, phonological judgment, and semantic judgment were significantly reduced between the patient and control groups with short SOA （P 〈 0.05）. However, different patterns of interaction between task 2 and SOA were observed across subject groups： subjects with stuttering were more strongly modulated by SOA when the second task was semantic judgment or phonological judgment （P 〈 0.05）, but not in the orthographic judgment experiment （P 〉 0.05）. These results indicated that the interaction mechanism between semantic processing and phonological encoding might be an underlying cause for stuttering.展开更多
The implementation of product development process management (PDPM) is an effective means of developing products with higher quality in shorter lead time. It is argued in this paper that product, data, person and acti...The implementation of product development process management (PDPM) is an effective means of developing products with higher quality in shorter lead time. It is argued in this paper that product, data, person and activity are basic factors in PDPM With detailed analysis of these basic factors and their relations in product developmed process, all product development activities are considered as tasks and the management of product development process is regarded as the management of task execution A task decomposition based product development model is proposed with methods of constructing task relation matrix from layer model and constraint model resulted from task decomposition. An algorithm for constructing directed task graph is given and is used in the management of tasks. Finally, the usage and limitation of the proposed PDPM model is given with further work proposed.展开更多
Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of...Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.展开更多
Genetic algorithm has been proposed to solve the problem of task assignment. However, it has some drawbacks, e.g., it often takes a long time to find an optimal solution, and the success rate is low. To overcome these...Genetic algorithm has been proposed to solve the problem of task assignment. However, it has some drawbacks, e.g., it often takes a long time to find an optimal solution, and the success rate is low. To overcome these problems, a new coarse grained parallel genetic algorithm with the scheme of central migration is presented, which exploits isolated sub populations. The new approach has been implemented in the PVM environment and has been evaluated on a workstation network for solving the task assignment problem. The results show that it not only significantly improves the result quality but also increases the speed for getting best solution.展开更多
Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delay...Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.展开更多
Poor plans of design project are often caused by the difficulties in realizing the underlying complexities and immeasurable characteristics in the deisgn process. To overcome this diffculty, a metric approach based on...Poor plans of design project are often caused by the difficulties in realizing the underlying complexities and immeasurable characteristics in the deisgn process. To overcome this diffculty, a metric approach based on the tasks analysis model of task importance degree was proposed. The model suggests that importance of a task can be measured through the influence to the project incurred by the imaginary failure of the task, which can be measured through three parts: the critical degree of a task to the whole project, the direct cost by the failure of a task, and the indirect cost on the other tasks affected by the failure of the task. The Analytic Hierarchy Process approach was applied to determine the critical degree and Case based Reasoning idea was used in detecting the implied error in the task. As an application case, a review work planning was given and some conclusions were arrived at.展开更多
An optimal algorithmic approach to task scheduling for, triplet based architecture（TriBA）, is proposed in this paper. TriBA is considered to be a high performance, distributed parallel computing architecture. TriBA ...An optimal algorithmic approach to task scheduling for, triplet based architecture（TriBA）, is proposed in this paper. TriBA is considered to be a high performance, distributed parallel computing architecture. TriBA consists of a 2D grid of small, programmable processing units, each physically connected to its three neighbors. In parallel or distributed environment an efficient assignment of tasks to the processing elements is imperative to achieve fast job turnaround time. Moreover, the sojourn time experienced by each individual job should be minimized. The arriving jobs are comprised of parallel applications, each consisting of multiple-independent tasks that must be instantaneously assigned to processor queues, as they arrive. The processors independently and concurrently service these tasks. The key scheduling issues is, when some queue backlogs are small, an incoming job should first spread its tasks to those lightly loaded queues in order to take advantage of the parallel processing gain. Our algorithmic approach achieves optimality in task scheduling by assigning consecutive tasks to a triplet of processors exploiting locality in tasks. The experimental results show that tasks allocation to triplets of processing elements is efficient and optimal. Comparison to well accepted interconnection strategy, 2D mesh, is shown to prove the effectiveness of our algorithmic approach for TriBA. Finally we conclude that TriBA can be an efficient interconnection strategy for computations intensive applications, if tasks assignment is carried out optimally using algorithmic approach.展开更多
A variation-aware task mapping approach is proposed for a multi-core network-on-chips with redundant cores, which includes both the design-time mapping and run-time scheduling algorithms. Firstly, a design-time geneti...A variation-aware task mapping approach is proposed for a multi-core network-on-chips with redundant cores, which includes both the design-time mapping and run-time scheduling algorithms. Firstly, a design-time genetic task mapping algorithm is proposed during the design stage to generate multiple task mapping solutions which cover a maximum range of chips. Then, during the run, one optimal task mapping solution is selected. Additionally, logical cores are mapped to physically available cores. Both core asymmetry and topological changes are considered in the proposed approach. Experimental results show that the performance yield of the proposed approach is 96% on average, and the communication cost, power consumption and peak temperature are all optimized without loss of performance yield.展开更多
With miscellaneous applications gener-ated in vehicular networks,the computing perfor-mance cannot be satisfied owing to vehicles’limited processing capabilities.Besides,the low-frequency(LF)band cannot further impro...With miscellaneous applications gener-ated in vehicular networks,the computing perfor-mance cannot be satisfied owing to vehicles’limited processing capabilities.Besides,the low-frequency(LF)band cannot further improve network perfor-mance due to its limited spectrum resources.High-frequency(HF)band has plentiful spectrum resources which is adopted as one of the operating bands in 5G.To achieve low latency and sustainable development,a task processing scheme is proposed in dual-band cooperation-based vehicular network where tasks are processed at local side,or at macro-cell base station or at road side unit through LF or HF band to achieve sta-ble and high-speed task offloading.Moreover,a utility function including latency and energy consumption is minimized by optimizing computing and spectrum re-sources,transmission power and task scheduling.Ow-ing to its non-convexity,an iterative optimization algo-rithm is proposed to solve it.Numerical results eval-uate the performance and superiority of the scheme,proving that it can achieve efficient edge computing in vehicular networks.展开更多
基金supported by the National Key R&D Plan of China(2024YFE0203600)the National Natural Science Foundation of China(62135009).
文摘To enhance the computational density and energy efficiency of on-chip neuromorphic hardware,this study introduces a novel network architecture for multi-task processing with in-memory optical computing.On-chip optical neural networks are celebrated for their capability to transduce a substantial volume of parameters into optical form while conducting passive computing,yet they encounter challenges in scalability and multitasking.Leveraging the principles of transfer learning,this approach involves embedding the majority of parameters into fixed optical components and a minority into adjustable electrical components.Furthermore,with deep regression algorithm in modeling physical propagation process,a compact optical neural network achieve to handle diverse tasks.In this work,two ultra-compact in-memory diffraction-based chips with integration of more than 60,000 parameters/mm^(2) were fabricated,employing deep neural network model and the hard parameter sharing algorithm,to perform multifaceted classification and regression tasks,respectively.The experimental results demonstrate that these chips achieve accuracies comparable to those of electrical networks while significantly reducing the power-intensive digital computation by 90%.Our work heralds strong potential for advancing in-memory optical computing frameworks and next generation of artificial intelligence platforms.
基金the China Postdoctoral Science Foundation,No.2001,#14the Capital Medical Development Science Research Program,No.2005-2003
文摘Stuttering is a common neurological deficit and its underlying cognitive mechanisms are a matter of debate, with evidence suggesting abnormal modulation between speech encoding and other cognitive components. Previous studies have mainly used single task experiments to investigate the disturbance of language production. It is unclear whether there is abnormal interaction between the three language tasks （orthographic, phonological and semantic judgment） in stuttering patients. This study used dual tasks and manipulated the stimulus onset asynchrony （SOA） between tasks 1 and 2 and the nature of the second task, including orthographic, phonological, and semantic judgments. The results showed that the performance records of orthographic judgment, phonological judgment, and semantic judgment were significantly reduced between the patient and control groups with short SOA （P 〈 0.05）. However, different patterns of interaction between task 2 and SOA were observed across subject groups： subjects with stuttering were more strongly modulated by SOA when the second task was semantic judgment or phonological judgment （P 〈 0.05）, but not in the orthographic judgment experiment （P 〉 0.05）. These results indicated that the interaction mechanism between semantic processing and phonological encoding might be an underlying cause for stuttering.
文摘The implementation of product development process management (PDPM) is an effective means of developing products with higher quality in shorter lead time. It is argued in this paper that product, data, person and activity are basic factors in PDPM With detailed analysis of these basic factors and their relations in product developmed process, all product development activities are considered as tasks and the management of product development process is regarded as the management of task execution A task decomposition based product development model is proposed with methods of constructing task relation matrix from layer model and constraint model resulted from task decomposition. An algorithm for constructing directed task graph is given and is used in the management of tasks. Finally, the usage and limitation of the proposed PDPM model is given with further work proposed.
文摘Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.
基金Supported by the Nation"86 3"Hi-Tech Development Program of China(86 3-30 6 -ZD11-0 1-8)
文摘Genetic algorithm has been proposed to solve the problem of task assignment. However, it has some drawbacks, e.g., it often takes a long time to find an optimal solution, and the success rate is low. To overcome these problems, a new coarse grained parallel genetic algorithm with the scheme of central migration is presented, which exploits isolated sub populations. The new approach has been implemented in the PVM environment and has been evaluated on a workstation network for solving the task assignment problem. The results show that it not only significantly improves the result quality but also increases the speed for getting best solution.
基金Supported by National Natural Science Foundation of China（60474035）,National Research Foundation for the Doctoral Program of Higher Education of China（20050359004）,Natural Science Foundation of Anhui Province（070412035）
基金supported by the National Science Foundation for Young Scholars of China(6130123471401175)
文摘Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.
文摘Poor plans of design project are often caused by the difficulties in realizing the underlying complexities and immeasurable characteristics in the deisgn process. To overcome this diffculty, a metric approach based on the tasks analysis model of task importance degree was proposed. The model suggests that importance of a task can be measured through the influence to the project incurred by the imaginary failure of the task, which can be measured through three parts: the critical degree of a task to the whole project, the direct cost by the failure of a task, and the indirect cost on the other tasks affected by the failure of the task. The Analytic Hierarchy Process approach was applied to determine the critical degree and Case based Reasoning idea was used in detecting the implied error in the task. As an application case, a review work planning was given and some conclusions were arrived at.
文摘An optimal algorithmic approach to task scheduling for, triplet based architecture（TriBA）, is proposed in this paper. TriBA is considered to be a high performance, distributed parallel computing architecture. TriBA consists of a 2D grid of small, programmable processing units, each physically connected to its three neighbors. In parallel or distributed environment an efficient assignment of tasks to the processing elements is imperative to achieve fast job turnaround time. Moreover, the sojourn time experienced by each individual job should be minimized. The arriving jobs are comprised of parallel applications, each consisting of multiple-independent tasks that must be instantaneously assigned to processor queues, as they arrive. The processors independently and concurrently service these tasks. The key scheduling issues is, when some queue backlogs are small, an incoming job should first spread its tasks to those lightly loaded queues in order to take advantage of the parallel processing gain. Our algorithmic approach achieves optimality in task scheduling by assigning consecutive tasks to a triplet of processors exploiting locality in tasks. The experimental results show that tasks allocation to triplets of processing elements is efficient and optimal. Comparison to well accepted interconnection strategy, 2D mesh, is shown to prove the effectiveness of our algorithmic approach for TriBA. Finally we conclude that TriBA can be an efficient interconnection strategy for computations intensive applications, if tasks assignment is carried out optimally using algorithmic approach.
文摘A variation-aware task mapping approach is proposed for a multi-core network-on-chips with redundant cores, which includes both the design-time mapping and run-time scheduling algorithms. Firstly, a design-time genetic task mapping algorithm is proposed during the design stage to generate multiple task mapping solutions which cover a maximum range of chips. Then, during the run, one optimal task mapping solution is selected. Additionally, logical cores are mapped to physically available cores. Both core asymmetry and topological changes are considered in the proposed approach. Experimental results show that the performance yield of the proposed approach is 96% on average, and the communication cost, power consumption and peak temperature are all optimized without loss of performance yield.
基金supported in part by National Natural Science Foundation of China(No.62071393)Fundamental Research Funds for the Central Universities(2682023ZTPY058).
文摘With miscellaneous applications gener-ated in vehicular networks,the computing perfor-mance cannot be satisfied owing to vehicles’limited processing capabilities.Besides,the low-frequency(LF)band cannot further improve network perfor-mance due to its limited spectrum resources.High-frequency(HF)band has plentiful spectrum resources which is adopted as one of the operating bands in 5G.To achieve low latency and sustainable development,a task processing scheme is proposed in dual-band cooperation-based vehicular network where tasks are processed at local side,or at macro-cell base station or at road side unit through LF or HF band to achieve sta-ble and high-speed task offloading.Moreover,a utility function including latency and energy consumption is minimized by optimizing computing and spectrum re-sources,transmission power and task scheduling.Ow-ing to its non-convexity,an iterative optimization algo-rithm is proposed to solve it.Numerical results eval-uate the performance and superiority of the scheme,proving that it can achieve efficient edge computing in vehicular networks.
