A neural network processing system includes one source node having a source memory and a source core, and one destination node having a destination memory and a destination core, the source core and the destination core being von-Neumann cores, the destination memory including weight data storage areas for storing weight data corresponding to each node, an accumulation memory for accumulating the weight data, and an event address memory, the destination core identifying the weight data storage area and accumulating the weight data to store the accumulated weight data in the accumulation memory, the source memory including a data set having first information for identifying the destination node and second information for identifying the weight data storage area, and the source core reading the data set and sending the second information in the data set to the destination node to conduct remote memory write.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A neural network processing system comprising a plurality of nodes including at least one source node and at least one destination node, the source node having a source memory and a source core, the destination node having a destination memory and a destination core, the source core and the destination core being von-Neumann cores, wherein: the destination memory includes one or more weight data storage areas to store weight data corresponding to each node accessing the destination memory, an accumulation memory to store an accumulated weight data, and an event address memory; the destination core identifies the weight data storage area corresponding to the source node based on information written to the event address memory, and accumulates the weight data to store the accumulated weight data in the accumulation memory; the source memory includes a data set having first information to identify the destination node and second information to identify the weight data storage area corresponding to the source node; and if a predetermined event occurs, the source core reads the data set from the source memory and sends the second information in the data set to the destination node to conduct noncoherent remote memory write to the event address memory in the destination memory. 2. The neural network processing system according to claim 1, wherein the predetermined event includes an event that the accumulated weight data stored in the accumulation memory reaches a predetermined threshold. 3. The neural network processing system according to claim 1, wherein: if the noncoherent memory write is conducted to the event address memory based on a write access from the source node, the event address memory is locked against other write accesses; and if the information written to the event address memory is read by the destination core, the event address memory is unlocked against the other write accesses. 4. The neural network processing system according to claim 1, wherein: the source core writes encoded source node information as the second information to the event address memory; and the destination core reads the weight data corresponding to the source node based on the encoded source node information written to the event address memory. 5. The neural network processing system according to claim 1, wherein: the destination core stores the information stored in the event address memory in a cache memory; and the information stored in the cache memory is invalidated if new data is written to the event address memory. 6. The neural network processing system according to claim 1, wherein: the destination memory includes a controller to access the destination core; and if new data is written to the event address memory, the controller interrupts a process of the destination core. 7. The neural network processing system according to claim 1, wherein the neural network processing system performs as a spiking neural network. 8. The neural network processing system according to claim 1, wherein: the plurality of nodes includes at least one intermediate node that mediates communication between the source node and the destination node; the intermediate node includes an intermediate storage area to store information sent from the source node; and a core in the intermediate node sends the information stored in the intermediate storage area to the destination node to conduct the noncoherent remote memory write to the event address memory in the destination memory. 9. The network processing system according to claim 1, wherein each node of the plurality of nodes is configured to perform both functions of the source node and the destination node. 10. A neural network processing system comprising a plurality of nodes, each node including a von-Neumann core and a memory, wherein: the memory includes one or more weight data storage areas to store weight data corresponding to each node accessing the memory, an accumulation memory to store an accumulated weight data, an event address memory, and a written data storage area to store a data set having first information for identifying one of the plurality of nodes and second information for identifying the weight data storage area corresponding to a respective node; the von-Neumann core identifies the weight data storage area, based on information written to the event address memory, corresponding to another one of the plurality of nodes having sent the information, and accumulates the weight data to store the accumulated weight data in the accumulation memory; and if the accumulated weight data stored in the accumulation memory reaches a predetermined threshold, the von-Neumann core reads the data set from the memory and sends the second information in the data set to conduct noncoherent remote memory write to the event address memory in the one of the plurality of nodes. 11. A neural network processing system comprising a plurality of nodes including at least one node including a plurality of cores and a memory, wherein: the plurality of cores includes a first core and a second core being von-Neumann cores; the memory includes one or more weight data storage areas to store weight data corresponding to each core, an accumulation memory to store an accumulated weight data, an event address memory for each core, and a written data storage area to store information for identifying each core; the first core sends the information for identifying the first core to conduct noncoherent remote memory write to the event address memory; the second core identifies the weight data based on the information written to the event address memory, and accumulates the weight data to store the accumulated weight data in the accumulation memory; and if the accumulated weight data stored in the accumulation memory reaches a predetermined threshold, the second core sends the information for identifying the second core to conduct the noncoherent remote memory write to the event address memory. 12. The neural network processing system according to claim 11, wherein: if the noncoherent remote memory write is conducted to the event address memory based on a write access from the first core, the event address memory is locked against other write accesses; and if the information written to the event address memory is read by the second core, the event address memory is unlocked against the other write accesses. 13. The neural network processing system according to claim 11, wherein: the first core writes encoded source node information for identifying the first core to the event address memory; and the second core reads the weight data corresponding to the first core based on the encoded source node information written to the event address memory.