Dynamic scheduling method and system for collaborative computing between CPU and GPU based on two-level scheduling
A dynamic scheduling and global scheduling technology, applied in the field of distributed computing, can solve problems such as the shortest task completion time, failure to fully utilize the cluster computing capacity, and inconsistent end times of computing nodes, so as to shorten the task processing time and realize pipeline processing. , Guaranteed not to wait for the effect of each other
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[0058] Example 1
[0059] like figure 1 Shown is the software framework diagram of the dynamic scheduling method of the present invention, figure 1 The global scheduling module can be deployed on any node and adopts active and standby redundancy to ensure reliability; the node scheduling module works on each node; the global scheduling module is responsible for distributing data blocks in the system according to the computing power of each node. Each node has two data storage queues, namely the current processing queue and the data cache queue; the current processing queue stores the data blocks being processed by the current CPU and GPU; the data cache queue stores network transmission to the local pending data block.
[0060] like figure 2 Shown is a schematic diagram of the data distribution of the global scheduling module. figure 2 The global scheduling module in the middle first determines the computing power weight of each node according to the parameters such as t...
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[0065] Example 2
[0066] Based on the same inventive concept as Embodiment 1, an embodiment of the present invention provides a dynamic scheduling system for collaborative computing between CPU and GPU based on two-level scheduling, including:
[0067] A system-level resource real-time monitoring module; the resource real-time monitoring module monitors the relevant parameters of the CPU and GPU in each node in real time; the relevant parameters include parameters such as the model of the CPU, the main frequency, the number of cores, and the average idle rate, And parameters such as GPU model, number of stream processors, etc.;
[0068] A global scheduling module; the global scheduling module receives the information sent by the resource real-time monitoring module, and estimates the processing capacity of each node in the system, according to the request of the node scheduling module in each node in batches according to the estimated processing of each node Ability to dynam...
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