Abstract: An embodiment is a traffic monitoring device configured to acquire traffic statistical information of a flow in the monitoring target network, determine whether the acquired traffic statistical information satisfies a predetermined reference for failure detection, capture packets of the flow determined to satisfy the predetermined reference as packets at the time of failure occurrence in the flow, and dynamically update the predetermined reference while the device is still acquiring traffic statistical information of the flow in the monitoring target network.

Abstract: An object detection device subjects fixed-length data having a decimal point position set therein to an arithmetic processing corresponding to respective layers in a plurality of layers configuring a multilayer neural network to which an input image is input, the arithmetic processing being performed in accordance with a processing algorithm for the multilayer neural network to which an input image is input. In the arithmetic processing, the object detection device counts the upper limit number of saturations, which is a number of times that upper limit value of a value range determined by the decimal point position is exceeded, and the lower limit number of saturations, which is a number of times that the lower limit value of the value range is not reached.

Abstract: A packet capturing device includes: a normal capturing function unit that accumulates packets that match conditions of a target flow registered in a flow table in response to an instruction to start capturing from outside and converts the accumulated packets into a captured file, from among packets flowing through a network that is a monitoring target; and a short-term capturing function unit that accumulates the packets received from the network during a period needed by the conditions of the target flow to be registered in the flow table from arrival of the instruction to start capturing and converts the accumulated packets into a captured file

Abstract: An embodiment is a packet capture device including a first local timer synchronized with an external global timer, a second local timer, a time stamp assign unit for assigning a time stamp to a inputted packet signal based on the second local timer, a filter unit for selecting the packet signal to which the time stamp is assigned, a capture file generation unit for receiving the selected packet signal, and a storage unit for storing a capture file generated in the capture file generation unit, wherein the capture file generation unit calculate a difference between a timer value of the first local timer and a timer value of the second local timer to correct the time stamp value on the basis of the difference.

Abstract: An object detecting device includes: an overall processing unit configured to perform object detection processing on an input image; an allocation processing unit configured to determine a segmented image for each frame which is subject to object detection among the plurality of segmented images in advance in a cycle of N frames, and reserve the determined segmented image; a selection processing unit configured to select and output, for each frame, some of the segmented images that are subject to object detection among the plurality of segmented images based on a reservation result from the allocation processing unit; a division processing unit configured to perform object detection processing on each of the segmented images output from the selection processing unit; and a synthesizing processing unit configured to synthesize an object detection result from the overall processing unit and an object detection result from the division processing unit.

Abstract: A first aspect of the present disclosure is a convolutional neural network inference processing device that performs processing in a convolutional neural network including a plurality of convolution layers and a residual layer that adds intermediate data related to the plurality of convolution layers as an addition target to a processing result by the plurality of convolution layers for each tile that is data obtained by dividing input data into a predetermined size, the convolutional neural network inference processing device including an inconsistency data storage unit that stores inconsistency data that is data at a portion where there is inconsistency between the processing result and the intermediate data, a past layer data storage unit that stores past layer data that is an addition target in a residual layer generated using inconsistency data related to the tile for which processing has been performed in a past and the intermediate data, and a processing unit that performs processing by the plurality o

Abstract: An embodiment packet capture method includes steps of imparting a flag for each data of a received and divided packet, a step of writing the data in a ring buffer, steps of issuing a failure detection trigger when a cumulative value of the number of bytes of the packet within a period of failure detection exceeds a failure detection threshold value, steps of stopping writing to the ring buffer when writing to the ring buffer reaches or exceeds a writing stop address determined on the basis of the failure detection trigger, a step of reading data sequentially from the writing stop address, and steps of outputting a packet capture depending on the result determined based on the flags of the read data.

Abstract: When an output feature map to be an output of convolution processing is output, the output feature map is output to a storage unit for each of divided small regions. When each small region is output to the storage unit, in a case where a feature included in the small region is the same as a predetermined feature or a feature of a small region output in the past, the predetermined feature or the feature of a small region output in the past is compressed and output to the storage unit.

Abstract: A packet capture device a packet analysis unit that analyzes an input packet; a flow identification unit that identifies a flow as a capture target; an output adjustment unit that adjusts a packet amount of the flow as the capture target to be output to a storage unit; a buffer unit that temporarily accumulates a packet of the flow as the capture target; and the storage unit that stores the packet of the flow as the capture target, in which the output adjustment unit is configured to decide whether to output the packet of the flow as the capture target to the storage unit for each predetermined measurement interval on the basis of a measurement result of the packet amount of the capture target in a predetermined measurement interval, and discard the packet not to be output to the storage unit.

Abstract: In a data processing device, a fixed-point position control unit determines, as first control. The fixed-point position control unit causes a detection calculation unit to perform calculation processing on processing target data at a processing point in time. The saturation rate control unit instructs, as second control to be repeated by the fixed-point position control unit, the fixed-point position control unit to move at least the fixed-point position as control to increase a lower limit saturation rate proportional to a magnitude of a counted lower limit counter value with respect to a result of the first control. The fixed-point position control unit performs, as the second control, a predetermined determination on the basis of the instruction from the saturation rate control unit and the metadata, determines the fixed-point position moved for each layer, and causes calculation processing to be performed.

Abstract: A traffic monitoring device includes an identification unit that identifies a flow of a packet received from a monitoring target network into a flow of a first flow group and a second flow group other than the first flow group on the basis of a rule table in which a predetermined rule is registered, a traffic aggregation unit that aggregates a traffic amount of the first flow group for each flow, an occurrence probability calculation unit that calculates an occurrence probability of each flow on the basis of a result of sampling at least some of the flow of the packet received, and a traffic estimation unit that estimates a traffic amount of each flow of the second flow group by multiplying the occurrence probability of each flow by the total value of the traffic amount of the second flow group.

Abstract: In a data processing device, a fixed-point position control unit determines, as first control. The fixed-point position control unit causes a detection calculation unit to perform calculation processing on processing target data at a processing point in time. The saturation rate control unit instructs, as second control to be repeated by the fixed-point position control unit, the fixed-point position control unit to move at least the fixed-point position as control to increase a lower limit saturation rate proportional to a magnitude of a counted lower limit counter value with respect to a result of the first control. The fixed-point position control unit performs, as the second control, a predetermined determination on the basis of the instruction from the saturation rate control unit and the metadata, determines the fixed-point position moved for each layer, and causes calculation processing to be performed.

Abstract: A calculation unit (22) sets each frame, of a moving image including a plurality of frames, as a target frame, calculates a motion vector with reference to a reference frame over an entirety of the target frames, and calculates an index indicating a magnitude of change between a key frame and the target frame, which is represented by using the motion vector, a judgement unit (25) judges whether or not the calculated index is equal to or greater than a predetermined threshold value, a first detection unit (27) detects a region indicating an object from the target frame by using an object detection model in a case in which the index is equal to greater than the threshold value, a second detection unit (28) detects a region on the target frame, which is obtained by correcting a position of a region detected in the reference frame by using the motion vector in a case in which the index is less than the threshold value, and an output unit (30) outputs information of the region detected by the first detection unit

Abstract: An object detection device 10 includes an entire processing unit 110 that obtains first metadata for the entire input image by scaling the input image and performing object detection processing, a divided image narrowing unit 120 that narrows down the input image into a predetermined number of selected divided images from a group of divided images obtained by dividing the input image, a division processing unit 130 that obtains second metadata by performing object detection processing for each of the selected divided images, and a synthesis processing unit 140 that removes the second metadata obtained by the division processing unit 130 that overlaps the first metadata obtained by the entire processing unit 110, and synthesizes the first metadata not removed and the first meta data obtained by the entire processing unit 110 to output the meta data.

Abstract: An embodiment is a packet capture device including a first local timer synchronized with an external global timer, a second local timer, a time stamp assign unit for assigning a time stamp to a inputted packet signal based on the second local timer, a filter unit for selecting the packet signal to which the time stamp is assigned, a capture file generation unit for receiving the selected packet signal, and a storage unit for storing a capture file generated in the capture file generation unit, wherein the capture file generation unit calculate a difference between a timer value of the first local timer and a timer value of the second local timer to correct the time stamp value on the basis of the difference.

Abstract: A packet capture system for capturing packets flowing in a capture target network, and a plurality of stages of packet distribution devices for capturing packet of a specific flow are cascade-connected, packet distribution devices identify a capture target flow by analyzing inputted packets, packet distribution devices other than a last-stage packet distribution device are configured to distribute packets to capture packets of a flow to be captured and output packets of a flow not to be captured to a next-stage packet distribution device, and the last-stage packet distribution device is configured to filter the packets of the flow to be captured and to discard the packets of the flow not to be captured.

Abstract: The integration unit 26, using configuration information of the convolutional neural network model and each filter used in each convolutional layer of the convolutional neural network model as inputs, deletes one or more pieces of activation function processing performed between the plurality of convolutional layers and integrates a plurality of filters used in the plurality of convolutional layers.

Abstract: An embodiment is a data processor including a decimal point position control circuit configured to set a decimal point position of N-bit (N is a natural number of 2 or more) fixed-length data corresponding to each of a plurality of layers constituting a multilayered neural network, and an arithmetic processing circuit configured to perform arithmetic processing corresponding to each of the plurality of layers constituting the multilayered neural network according to a processing algorithm of the multilayered neural network on the N-bit fixed-length data for which the decimal point position has been set by the decimal point position control circuit.

Abstract: A network load balancing apparatus has a data buffer for each communication path of a received packet's transfer destinations, calculates a first hash value using a field value contained in the packet, determines, based on the field value of the packet or the first hash value, a communication path of a transfer destination of the packet subject to external transfer control for transmission to a predetermined external server, determines, based on the first hash value, a communication path of a transfer destination of the packet to be subject to priority control, determines, based on a second hash value based on the first hash value, a communication path of a transfer destination of the packet to be subject to load balancing control, to match a preset load balancing situation of the data buffer, and transmits the packet to a data buffer corresponding to the communication path of the transfer destination.

Abstract: A network load balancing apparatus has a data buffer provided to each communication path of transfer destinations of a received packet and being associated with a virtual function, determines a destination virtual function based on a field value of the received packet, determines a communication path of a transfer destination of a packet to be subject to priority control based on a first hash value calculated using the field value, determines a communication path of a transfer destination of a packet to be subject to load balancing control, to match a preset load balancing situation of the data buffer, based on a second hash value based on the first hash value, and transmits the packet to a data buffer corresponding to the destination virtual function and the communication path of the transfer destination.