Abstract: An embodiment is a computer system for processing input data, the system including a plurality of calculators, and a host connected to the plurality of calculators configured to control the plurality of calculators, wherein the processed data is configured to be transferred between the plurality of calculators, the calculator includes a trace buffer configured to record trace data upon detection of a predetermined event from the input data, and the trace data has a timestamp value that is the detection time of the event.

Abstract: A computing machine is a computing machine capable of adding or deleting a computational resource R for processing input data input from outside, and includes: a state information acquisition unit that acquires state information indicating a state of the computing machine; and a performance estimation unit that estimates, on the basis of the state indicated by the state information, a change in processing performance of the computing machine when at least one of dynamic addition or deletion of a computational resource or an increase in data amount of the input data or output data occurs.

Abstract: AI inference system includes an encoder circuit that encodes an image captured by a camera, a decoder circuit that decodes the image, a first inference processing unit that executes first inference processing on the decoded image for each frame, a second inference processing unit that executes second inference processing with higher accuracy than the first inference only for frames of an image whose confidence value of the first inference exceeds a predetermined threshold, and a frame rate control unit that reduces frame rates of the encoder circuit and the decoder circuit from an initial value to a low speed value when the confidence value is equal to or less than the predetermined threshold.

Abstract: A computing system includes top-of-rack switches, a spine switch, and PIN blades arranged between the top-of-rack switches and resource blades. Each of the PIN blades includes a plurality of processing blocks, and each of the processing blocks includes a functional unit that performs predetermined processing on data included in the received packet.

Abstract: An embodiment is an electronic computer including a plurality of arithmetic circuits which sequentially execute a plurality of processings on a processing data, and a controller which executes a program and performs a control of causing the plurality of arithmetic circuits to sequentially execute the plurality of processings. An arithmetic circuit ID is imparted to each of the plurality of arithmetic circuits, the plurality of arithmetic circuits include a first arithmetic circuit that executes a first processing among the plurality of processings, and a second arithmetic circuit that executes a second processing that executes processing on a processing result of the first processing among the plurality of processings, and the first arithmetic circuit transmits the processing result of the first processing to the arithmetic circuit ID of the second arithmetic circuit as a destination.

Abstract: The electrofusion joint includes a tubular main body, a stopper portion, a first heat generating section, and a second heat generating section. The tubular main body includes a joint receiving portion. The stopper portion projects inward on the inner surface of the main body. The first heat generating section includes a heating wire wound and arranged at the joint receiving portion. The second heat generating section includes a heating wire wound so that wound parts are adjacent to each other and the heating wire is disposed in the stopper portion. The first heat generating section includes at least one heat generating portion in which the heating wire is wound so that the wound parts are adjacent to each other.

Abstract: An embodiment is a computer system which processes input data which includes a plurality of arithmetic parts; and a host part connected to the plurality of arithmetic parts and configured to control the plurality of arithmetic parts, in which the processed data is transferred between the plurality of arithmetic parts, the arithmetic part includes trace parts which record trace data using detection of a predetermined event from the input data as a trigger, the trace data has a timestamp value which is a detection time of the event based on an operating frequency of the arithmetic part, and the timestamp values of the plurality of arithmetic parts are synchronized.

Abstract: A distributed deep learning system that can achieve speeding-up by processing learning in parallel at a large number of learning nodes connected with a communication network and perform faster cooperative processing among the learning nodes connected through the communication network is provided. The distributed deep learning system includes: a plurality of computing interconnect devices 1 connected with each other through a ring communication network 3 through which communication is possible in one direction; and a plurality of learning nodes 2 connected with the respective computing interconnect devices 1 in a one-to-one relation, and each computing interconnect device 1 executes communication packet transmission-reception processing between the learning nodes 2 and All-reduce processing simultaneously in parallel.

Abstract: Each NIC performs an aggregation calculation of data output from each processor in a normal order including a head NIC located at a head position of a first pipeline connection, an intermediate NIC located at an intermediate position, and a tail NIC located at a tail position, and when the aggregation calculation in the tail NIC is completed, each NIC starts distribution of an obtained aggregation result, distributes the aggregation result in a reverse order including the tail NIC, the intermediate NIC, and the head NIC, and outputs the aggregation result to the processor of the communication interface.

Abstract: A distributed processing node includes a computing device that calculates gradient data of a loss function from an output result obtained by inputting learning data to a learning target model, an interconnect device that aggregates gradient data between the distributed processing node and other distributed processing nodes, a computing function unit that is provided in a bus device and performs processing of gradient data from the computing device, and a DMA controller that controls DMA transfer of gradient data between the computing device and the bus device and DMA transfer of gradient data between the bus device and the interconnect device.

Abstract: The present disclosure provides a medical image processing apparatus capable of readily creating, from a medical image, an electronic document that displays a three-dimensional body organ model. The medical image processing apparatus performs control to acquire patient information from DICOM additional information of medical image data designated when the creation of the electronic document has been instructed, and to create the electronic document of the three-dimensional body organ model corresponding to the medical image data, the electronic document containing the acquire patient information. To which patient the three-dimensional body organ model belongs can be identified on the electronic document.

Abstract: A plurality of analysis functions each corresponding to an organ are managed, and organ information is stored in such a manner as to correlate with a corresponding type of analysis function. The organ information indicates which of a plurality of regions included in the organ is to be subjected to thinning. Specification of one of the analysis functions is received from a user, and medical image data is acquired. A plurality of regions of an organ included in the acquired medical image data are identified. The identified plurality of regions of the organ, a region to be subjected to thinning is determined on the basis of the stored organ information and the received type of the analysis function. Thinning is performed on the determined region of the organ. An image of the thinned region is displayed together with an image of a region not subjected to thinning.

Abstract: An information processing apparatus includes circuitry and a memory, the circuitry performing perceptual image conversion of converting two image data generated from one color image data respectively into perceptual images based on human visual characteristics, collation of determining whether the two perceptual images converted by the perceptual image conversion are same, and comparison result outputting of outputting the comparison result by the collation.

Abstract: An information processing apparatus includes circuitry configured to display a first image, a second image, a difference image indicating difference between the first image and the second image, and types of the difference.

Abstract: An information processing device includes circuitry to generate difference information related to a difference between a first image and a second image. The difference information has a plurality of areas. The circuitry further obtains a total value of differences in each of the plurality of areas as one of a plurality of total area difference amounts and determines whether the first image is same as the second image based on each of the plurality of total area difference amounts.

Abstract: Medical image data is identified, and a lung field region and an emphysema region in each of a plurality of tomographic images are extracted. A mechanism is provided, which is capable of calculating the ratio of the emphysema region to the lung field region, and displaying an image of the medical image data and a value representing the calculated ratio in association with each other.

Abstract: An information processing apparatus includes circuitry and a memory, the circuitry performing perceptual image conversion of converting two image data generated from one color image data respectively into perceptual images based on human visual characteristics, collation of determining whether the two perceptual images converted by the perceptual image conversion are same, and comparison result outputting of outputting the comparison result by the collation.

Abstract: A plurality of analysis functions each corresponding to an organ are managed, and organ information is stored in such a manner as to correlate with a corresponding type of analysis function. The organ information indicates which of a plurality of regions included in the organ is to be subjected to thinning. Specification of one of the analysis functions is received from a user, and medical image data is acquired. A plurality of regions of an organ included in the acquired medical image data are identified. The identified plurality of regions of the organ, a region to be subjected to thinning is determined on the basis of the stored organ information and the received type of the analysis function. Thinning is performed on the determined region of the organ. An image of the thinned region is displayed together with an image of a region not subjected to thinning.

Abstract: A plurality of analysis functions each corresponding to an organ are managed, and organ information is stored in such a manner as to correlate with a corresponding type of analysis function. The organ information indicates which of a plurality of regions included in the organ is to be subjected to thinning. Specification of one of the analysis functions is received from a user, and medical image data is acquired. A plurality of regions of an organ included in the acquired medical image data are identified. The identified plurality of regions of the organ, a region to be subjected to thinning is determined on the basis of the stored organ information and the received type of the analysis function. Thinning is performed on the determined region of the organ. An image of the thinned region is displayed together with an image of a region not subjected to thinning.

Abstract: The present disclosure provides a medical image processing apparatus capable of readily creating, from a medical image, an electronic document that displays a three-dimensional body organ model. The medical image processing apparatus performs control to acquire patient information from DICOM additional information of medical image data designated when the creation of the electronic document has been instructed, and to create the electronic document of the three-dimensional body organ model corresponding to the medical image data, the electronic document containing the acquire patient information. To which patient the three-dimensional body organ model belongs can be identified on the electronic document.