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公开(公告)号:US20210256346A1
公开(公告)日:2021-08-19
申请号:US16794062
申请日:2020-02-18
Inventor: Giuseppe DESOLI , Carmine CAPPETTA , Thomas BOESCH , Surinder Pal SINGH , Saumya SUNEJA
Abstract: Embodiments of an electronic device include an integrated circuit, a reconfigurable stream switch formed in the integrated circuit along with a plurality of convolution accelerators and a decompression unit coupled to the reconfigurable stream switch. The decompression unit decompresses encoded kernel data in real time during operation of convolutional neural network.
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公开(公告)号:US20210192833A1
公开(公告)日:2021-06-24
申请号:US17194055
申请日:2021-03-05
Inventor: Surinder Pal SINGH , Thomas BOESCH , Giuseppe DESOLI
IPC: G06T15/08 , G06T7/62 , G06T7/11 , G06F16/901 , G06F9/38 , G06K9/00 , G06K9/62 , G06N3/08 , G06N3/04 , G06N3/063
Abstract: A device include on-board memory, an applications processor, a digital signal processor (DSP) cluster, a configurable accelerator framework (CAF), and at least one communication bus architecture. The communication bus communicatively couples the applications processor, the DSP cluster, and the CAF to the on-board memory. The CAF includes a reconfigurable stream switch and data volume sculpting circuitry, which has an input and an output coupled to the reconfigurable stream switch. The data volume sculpting circuitry receives a series of frames, each frame formed as a two dimensional (2D) data structure, and determines a first dimension and a second dimension of each frame of the series of frames. Based on the first and second dimensions, the data volume sculpting circuitry determines for each frame a position and a size of a region-of-interest to be extracted from the respective frame, and extracts from each frame, data in the frame that is within the region-of-interest.
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公开(公告)号:US20210072894A1
公开(公告)日:2021-03-11
申请号:US17012501
申请日:2020-09-04
Inventor: Nitin CHAWLA , Giuseppe DESOLI , Anuj GROVER , Thomas BOESCH , Surinder Pal SINGH , Manuj AYODHYAWASI
Abstract: A memory array arranged as a plurality of memory cells. The memory cells are configured to operate at a determined voltage. A memory management circuitry coupled to the plurality of memory cells tags a first set of the plurality of memory cells as low-voltage cells and tags a second set of the plurality of memory cells as high-voltage cells. A power source provides a low voltage to the first set of memory cells and provides a high voltage to the second set of memory cells based on the tags.
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公开(公告)号:US20190266479A1
公开(公告)日:2019-08-29
申请号:US16280991
申请日:2019-02-20
Inventor: Surinder Pal SINGH , Thomas BOESCH , Giuseppe DESOLI
Abstract: Embodiments of a device include an integrated circuit, a reconfigurable stream switch formed in the integrated circuit along with a plurality of convolution accelerators and an arithmetic unit coupled to the reconfigurable stream switch. The arithmetic unit has at least one input and at least one output. The at least one input is arranged to receive streaming data passed through the reconfigurable stream switch, and the at least one output is arranged to stream resultant data through the reconfigurable stream switch. The arithmetic unit also has a plurality of data paths. At least one of the plurality of data paths is solely dedicated to performance of operations that accelerate an activation function represented in the form of a piece-wise second order polynomial approximation.
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公开(公告)号:US20180189229A1
公开(公告)日:2018-07-05
申请号:US15423272
申请日:2017-02-02
Inventor: Giuseppe DESOLI , Thomas BOESCH , Nitin CHAWLA , Surinder Pal SINGH , Elio GUIDETTI , Fabio Giuseppe DE AMBROGGI , Tommaso MAJO , Paolo Sergio ZAMBOTTI
Abstract: Embodiments are directed towards a system on chip (SoC) that implements a deep convolutional network heterogeneous architecture. The SoC includes a system bus, a plurality of addressable memory arrays coupled to the system bus, at least one applications processor core coupled to the system bus, and a configurable accelerator framework coupled to the system bus. The configurable accelerator framework is an image and deep convolutional neural network (DCNN) co-processing system. The SoC also includes a plurality of digital signal processors (DSPs) coupled to the system bus, wherein the plurality of DSPs coordinate functionality with the configurable accelerator framework to execute the DCNN.
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