Fujitsu Corporation

Canon Kabushiki Kaisha

Fujitsu General Limited

Nissan Motor Company Limited

Hitachi Powdered Metals Co., Ltd.

Fujitsu Semiconductor Limited

Denso Corporation

Honda Giken Kogyo Kabushiki Kaisha

Nippon Sanso Kabushiki Kaisha

Takashi Suzuki

Manabu Hongo

Hiroaki Matsuda

Noriyoshi Shimizu

Hidekatsu Kobayashi

Tatsuhito Araki

Hidehiko Hizuka

Kouki Murakami

Katsuhiko Mori

Yoshiyuki Nakao

Wataru Murata

Kenji Narita

Hiroki Kondo

Yuji Kaneda

Satoshi Sudo

Yuji Souma

Yoshichika Fukuda

Koji Kawanishi

Yuji Kawai

Hiroyuki Okudera

Masakazu Matsugu

Hiroshi Kubo

Toshio Yoshida

Yoshiya Matsumoto

Kei Ishii

Ryohei Okazaki

Tomoyuki Nagamine

Haruyoshi Yada

Kazunori Murayama

Tadayuki Tsutsui

Nobuyuki Nishikawa

Takeshi Komuro

Kotaro Yano

Kenichi Watanabe

Yoshinori Ito

Masami Kato

Yutaka Mabuchi

Masaki Ukai

Nobuyuki Ohtsuka

Takashi Murata

Akira Fujiki

Kan Torii

Kiyotaka Takahashi

Yasunobu Akizuki

Hiroaki Sakashita

Hisaya Sakai

Masanobu Ikeda

Takehisa Ishikawa

Kiyoshi Ozawa

Ryo Hattori

Yukihiro Maekawa

Takuya Nishino

Kurumi Harada

Jyun-ichi Yamada

Masaki Yamada

Mitsuru Sato

Kazuaki Kurihara

Yusuke Mitarai

Kenta Suzuki

Akira Takashima

Hirofumi Watatani

Shun-ichi Fukuyama

Yoshifumi Kajiwara

Hayato Matsuda

Hideki Kitada

Satoshi Otsuka

Shunsuke Nakano

Hideo Shikata

Tomonori Kojima

Toyoji Sawada

Hiroyuki Takita

Masanori Murakami

Norihito Gomyo

Hideo Urata

Yoshihiro Tanimura

Kazuyuki Imamura

Yoichi Tanabe

Yuichi Shibukawa

Yoshikazu Kumagaya

Megumi Yokoi

Takushi Fujioka

Tsutomu Hosoda

Fumihiko Ando

Mitsuaki Igeta

Tomoki Nishio

Yoshihiro Matsuoka

Atsushi Fusejima

Hisanari Fujita

Hajime Sasaki

Jun-ichi Ichikawa

Kazunari Kosakai

Kazuhiro Tada

Seiji Hirao

Kotaro Kuwahara

Toshiro Ito

Masao Oshima

Noriyuki Shimizu

Kenkichi Itoh

Jyunji Osako

An arithmetic processing apparatus includes weight tables each configured to store weighting factors in one-to-one correspondence with indexes associated with instruction addresses, a first weight arithmetic unit configured to perform a first operation and a second operation based on the weighting factors retrieved from the weight tables in response to an instruction fetch address, the first operation producing a first value for branch prediction for the instruction fetch address, the second operation producing second values for future branch prediction, and a second weight arithmetic unit configured to perform, in parallel with the second operation, a third operation equivalent to the second operation based on the weighting factors retrieved from the weight tables in response to an address of a completed branch instruction, wherein the second values stored in the first weight arithmetic unit are replaced with the third values upon detection of a wrong branch prediction.

Arithmetic processing apparatus which replaces values for future branch prediction upon wrong branch prediction

An arithmetic processing device includes: a pipeline circuit including an instruction fetch circuit, an instruction decoder that performs a first branch misprediction determination for a branch instruction, and issues the instructions in-order, a branch instruction processing circuit which performs a second branch misprediction determination for the branch instruction; and a commit processing circuit that executes a commit processing of the processed instructions in-order. When a branch misprediction is established in the first branch misprediction determination, the instruction decoder inhibits issuing of the instructions to the branch prediction destination from the instruction decoder, and when the first branch instruction for which the branch misprediction is established is inputted, the branch instruction processing circuit clears the pipeline state in the instruction decoder, allows the instruction fetch circuit to start fetching instructions to a correct branch destination, and releases the inhibit of issuing of the instructions from the instruction decoder.

Arithmetic processing device and control method for arithmetic processing device

An arithmetic processing device includes: a branch prediction unit configured to predict a branch destination address and loop processing based on an address generated by an address generation unit; an instruction buffer unit configured to store an instruction of the address generated by the address generation unit; an instruction decoding unit configured to decode the instruction stored in the instruction buffer unit; and a loop buffer unit configured to store decoding results or decoding intermediate results of instructions of the predicted loop processing that are decoded by the instruction decoding unit and output the stored decoding results or decoding intermediate results a predetermined number of times in response to the loop processing, in which during a period when selecting the output of the loop buffer unit, operations of the address generation unit, the branch prediction unit, the instruction buffer unit, and the instruction decoding unit are stopped.

Arithmetic processing device for predicting loop processing

A processor includes: an instruction execution unit that executes an instruction; and a branch prediction unit that stores history information indicating every instruction fetches performed a certain number of times before an instruction fetch of a branch prediction target instruction whether the instruction predicted as branch-taken is included and weight tables including weights corresponding to instructions and predicts the branch prediction target instruction to be taken or not-taken. The branch prediction unit, before the instruction fetch of the branch prediction target instruction, obtains the history information and the weights related to the instruction fetches performed the certain number of times to perform a product-sum operation, and at the time of the instruction fetch of the branch prediction target instruction, performs an operation of a result of the product-sum operation and a weight of the branch prediction target instruction to perform branch prediction.

Dynamic branch predictor indexing a plurality of weight tables by instruction address fetch history and making a prediction based on a product sum calculation of global history register values and outputted weight table value

A power generating apparatus according to an aspect of the invention includes a plurality of pn stacks, each formed by stacking a p-type semiconductor layer and an n-type semiconductor layer one on top of the other, and a mode switching unit which effects switching to a photovoltaic power generation mode or a thermal power generation mode by connecting the plurality of pn stacks with each other. The mode switching unit effects switching to the photovoltaic power generation mode by connecting the p-type semiconductor layers in parallel with each other and the n-type semiconductor layers in parallel with each other between the plurality of pn stacks. The mode switching unit effects switching to the thermal power generation mode by connecting the p-type semiconductor layer and the n-type semiconductor layerin series between different ones of the pn stacks.

Power generating apparatus and power generating system equipped with such power generating apparatus

An arithmetic processing device includes: first prediction units which output branch prediction information of a fetched conditional branch instruction based on past branch history information of conditional branch instructions; a second prediction unit which stores a branch taken consecutive number of times and a branch not-taken consecutive number of times to a pattern information storage unit, and outputs branch prediction information of a fetched conditional branch instruction based on the past branch taken consecutive number of times or branch not-taken consecutive number of times stored; selecting units which selectively output the branch prediction information output from the first prediction units or the second prediction unit; and a selector which outputs a next instruction address of the conditional branch instruction or a branch target address of the conditional branch instruction to an instruction fetch unit in accordance with the branch prediction information output by the selecting units.

Arithmetic processing device and control method of arithmetic processing device

A pattern recognition apparatus that is lightweight for mounting, and reduces the effects of registration conditions or check conditions on recognition accuracy. Similarity sets for respective local features are calculated from a local feature of input data and local features of a plurality of pieces of dictionary data corresponding to the local feature of the input data. Integrated similarities are calculated by integrating a plurality of similarity sets in the local features according to a registration condition or a check condition. Dictionary data corresponding to the input data is identified based on the calculated integrated similarities.

Pattern recognition apparatus and pattern recognition method that reduce effects on recognition accuracy, and storage medium

A thermoelectric conversion module includes: a first substrate having water permeability and thermal conductivity; a thermoelectric conversion element provided on the first substrate; a heat insulator having water permeability provided around the thermoelectric conversion element on the first substrate; and a second substrate disposed on the thermoelectric conversion element and the heat insulator and having water permeability and thermal conductivity.

Thermoelectric conversion module

A pattern recognition apparatus that recognizes a data attribute of input data calculates correlation values of feature quantities of corresponding local patterns between the input data and dictionary data for each of a plurality of dictionary data prepared for each data attribute, combines, for each data attribute, the calculated correlation values of local patterns of each dictionary datum to acquire a set of correlation values of each data attribute, integrates correlation values included in each set of correlation values of each data attribute to calculate a similarity of the input data for each data attribute, and identifies the data attribute of the input data based on the calculated similarity.

Pattern recognition method and pattern recognition apparatus

A processor includes: first selectors that select instruction addresses of instructions of a plurality of threads or a branch target address of a branch instruction to be predicted and that output addresses of the plurality of threads; a second selector that selects one of the addresses of the plurality of threads output by the first selectors; a branch prediction circuit that predicts and outputs a branch direction, which indicates whether the branch instruction of the address selected by the second selector is branched, based on the selected address in a first cycle stage and that predicts and outputs the branch target address of the branch instruction to be predicted based on the selected address in a second cycle stage later than the first cycle stage; and a thread arbitration circuit that controls selection of the addresses of the threads by the first selectors and the second selector.

Processor and control method of processor

A dictionary data registration apparatus includes a dictionary configured to be registered a local feature amount for each region of an image with respect to each of a plurality of categories, an extraction unit configured to extract the local feature amount from a plurality of regions of an input image, a selection unit configured to select a plurality of the local feature amounts for each region according to a distribution of the local feature amounts extracted by the extraction unit from a plurality of regions of a plurality of pieces of input images which belongs to the category with respect to each of the plurality of categories, and a registration unit configured to register the selected plurality of local feature amounts on the dictionary as a local feature amount for each region with respect to the category.

Dictionary data registration apparatus for image recognition, method therefor, and program

A method for determining feature point locations in an image performs a first search in a predetermined first search area to search for locations of plural feature points in the image, corrects the locations of the plural feature points based on a geometric layout relationship among the plural feature points searched for, sets a second search area based on the corrected location of each of the feature points, and performs a second search in the second search area to search for the location of each of the feature points. Then, the method determines reliability of the location of each feature point searched for by the second search and selects one of the corrected location and the location searched for by the second search, as a location of the feature point.

Feature point location determination method and apparatus

A semiconductor device includes a semiconductor substrate, a heat generating device, and a heat radiating part. The heat generating device is provided on the semiconductor substrate, and the heat radiating part is provided above the heat generating device. The heat radiating part is thermally coupled with the semiconductor substrate through at least one contact part.

Semiconductor device for effectively disperse heat generated from heat generating device

An image recognition apparatus comprising: an obtaining unit configured to obtain one or more images; a detection unit configured to detect a target object image from each of one or more images; a cutting unit configured to cut out one or more local regions from the target object image; a feature amount calculation unit configured to calculate a feature amount from each of one or more local regions to recognize the target object; a similarity calculation unit configured to calculate, for each of one or more local regions, a similarity between the feature amounts; and a registration unit configured to, if there is a pair of feature amounts whose similarity is not less than a threshold, register, for each of one or more regions, one of the feature amounts as dictionary data for the target object.

Dictionary creation using image similarity

A person is detected as a subject from an image obtained by image capture, and information, for example, the number of such subjects, is obtained as subject-related information. Then, the greater the number of subjects, the more a setting of a condition that the subjects should satisfy is relaxed. As a result, in an image processing apparatus having a function that identifies a subject state, the usability of that function that identifies the subjects can be improved even in a case in which multiple subjects are present.

Image processing apparatus and control method for same

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Kawasaki, Japan

Takashi Suzuki