A distributed processing method of a system including N distributed processing nodes, wherein N is an integer of 2 or greater, disposed in a ring shape and connected to adjacent nodes via a communication path in which an n-th distributed processing node, wherein n=1, . . . , N, includes a first communication port for performing simultaneous bidirectional communication with an n+-th distributed processing node, wherein n+=n+1 provided that n+=1 if n=N, and a second communication port for performing simultaneous bidirectional communication with an n−-th distributed processing node, wherein n−=n−1 provided that n−=N if n=1, the distributed processing method comprising:
- a first step at each of the distributed processing nodes of generating distributed data for each of M weights w [m] of a neural network of a learning target, wherein M is an integer of 2 or greater and m=1, . . . , M;
- a second step, at a first distributed processing node specified in advance out of the N distributed processing nodes, of using the distributed data generated in the first distributed processing node as first consolidated data, packetizing the first consolidated data in order of numbers m of the weights w [m], and transmitting the first consolidated data from the first communication port of the first distributed processing node to a second distributed processing node;
- a third step, at a k-th distributed processing node out of the N distributed processing nodes except the first distributed processing node, of generating updated first consolidated data by calculating a sum of the first consolidated data received via the second communication port of the k-th distributed processing node from a (k−1)-th distributed processing node and the distributed data generated in the k-th (k=2, . . . , N) distributed processing node for each corresponding one of the weights w [m], packetizing the first consolidated data in the order of the numbers m, and transmitting the first consolidated data from the first communication port of the k-th distributed processing node to a k+-th distributed processing node, wherein k+=k+1 or k+=1 if k=N;
- a fourth step at the first distributed processing node of using the first consolidated data received via the second communication port of the first distributed processing node from an N-th distributed processing node as second consolidated data, packetizing the second consolidated data in the order of the numbers m, and transmitting the second consolidated data from the second communication port of the first distributed processing node to the N-th distributed processing node;
- a fifth step at the k-th distributed processing node of packetizing the second consolidated data received via the first communication port of the k-th distributed processing node from the k+-th distributed processing node in the order of the numbers m, and transmitting the second consolidated data from the second communication port of the k-th distributed processing node to the (k−1)-th distributed processing node;
- a sixth step at the first distributed processing node of receiving the second consolidated data from the second distributed processing node via the first communication port of the first distributed processing node;
- a seventh step at each distributed processing node of updating the weights w [m] of the neural network, based on the received second consolidated data;
- an eighth step at the first distributed processing node of measuring an aggregation communication time period required by each of the distributed processing nodes to consolidate the distributed data or an aggregation dispatch communication time period being a total time period of the aggregation communication time period and a time period required by each of the distributed processing nodes to dispatch the second consolidated data;
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- a ninth step at the first distributed processing node of issuing a warning indicating a consolidation delay anomaly when the aggregation communication time period or the aggregation dispatch communication time period exceeds a predetermined maximum consolidation delay time period.