Distributed high-performance computing method based on virtual tree network technology
A high-performance computing and tree-type network technology, applied in the field of computer distributed computing, can solve problems that are not suitable for parallel computing
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Embodiment approach 1
[0012] Implementation plan 1 of this case: solving the knapsack problem.
[0013] Solving a problem requires discovering methods that can be recursively divided into subproblems. The knapsack problem is an NP problem. When the scale is large, a single computer cannot do it. Suppose a knapsack problem has 100 elements; we can divide this knapsack problem into 1024 knapsack problems containing 90 elements (find the combined value of the first 10 elements); and this knapsack problem containing 90 elements It can be divided into 1024 knapsack problems containing 80 elements; and so on, until it can be decomposed into a knapsack problem that can be completed for a single computer (such as a 20-element knapsack problem).
[0014] Assignment and routing of divided subproblems. Suppose a certain computer needs to solve the knapsack problem with 100 elements; it is judged that the calculation cannot be completed alone; this computer knapsack problem is divided into 1024 knapsack p...
Embodiment approach 2
[0042] Implementation plan 2 of this case: MPI front desk agent. As in the implementation scheme 1 of this case, if a supercomputer has 10,000 nodes, the 10,000 nodes can be processed as a computer to form a virtual organizational structure; an ordinary computer can also be used as a front desk agent, and when subtasks are assigned to the front desk The agent, according to the settings and calculations, will divide a supercomputer-computable subtask and other subtasks. The subtasks of the computer can be sent to the supercomputer for calculation (maybe using MPI calculation), and the other subtasks are assigned to the lower virtual group computers.
Embodiment approach 3
[0043] Embodiment 3 of this case: Multiple calculation modes of computer nodes. Computer node computing can adopt various computing methods such as thread parallelism and GPU parallelism according to settings and calculations. If it is found that the computer node supports GPU computing, the computer can download the GPU components that solve this problem from the server for calculation.
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