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公开(公告)号:US20210334445A1
公开(公告)日:2021-10-28
申请号:US17238128
申请日:2021-04-22
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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公开(公告)号:US11853677B2
公开(公告)日:2023-12-26
申请号:US18082392
申请日:2022-12-15
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06F30/398 , G06N3/08
CPC classification number: G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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3.
公开(公告)号:US20240143885A1
公开(公告)日:2024-05-02
申请号:US17973078
申请日:2022-10-25
Applicant: Google LLC
Inventor: Myung-Chul Kim , Roger David Carpenter , Debjit Sinha , Paul Kingsley Rodman , Xuyang Jin , Young-Joon Lee
IPC: G06F30/392 , G06F30/398
CPC classification number: G06F30/392 , G06F30/398
Abstract: Aspects of the disclosure provide for eliminating or reducing uniquification of blocks in a chip-level graph of a computer chip, to reduce the size of the graph while still encoding block-specific information. For each group of blocks in the graph generated from a multiply-instantiated block (MIB), a block in the group is selected as a base block. The physical position of the base block is encoded in a reduced graph, and the physical positions of the remaining blocks are encoded as a linear transformation of the physical position of the base block across the face of the chip. Each group of blocks instantiated from the same MIB is represented as a single instance. The reduced graph can be fed into a device configured to perform a circuit component placement process, to identify the placement of circuit components for blocks in the chip in accordance with one or more objectives.
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公开(公告)号:US11556690B2
公开(公告)日:2023-01-17
申请号:US17555085
申请日:2021-12-17
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/39 , G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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公开(公告)号:US20220108058A1
公开(公告)日:2022-04-07
申请号:US17555085
申请日:2021-12-17
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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公开(公告)号:US12248745B2
公开(公告)日:2025-03-11
申请号:US18395251
申请日:2023-12-22
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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公开(公告)号:US20240249058A1
公开(公告)日:2024-07-25
申请号:US18395251
申请日:2023-12-22
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06F30/398 , G06N3/08
CPC classification number: G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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公开(公告)号:US20230117786A1
公开(公告)日:2023-04-20
申请号:US18082392
申请日:2022-12-15
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06F30/398 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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公开(公告)号:US11216609B2
公开(公告)日:2022-01-04
申请号:US17238128
申请日:2021-04-22
Applicant: Google LLC
Inventor: Anna Darling Goldie , Azalia Mirhoseini , Ebrahim Songhori , Wenjie Jiang , Shen Wang , Roger David Carpenter , Young-Joon Lee , Mustafa Nazim Yazgan , Chian-Min Richard Ho , Quoc V. Le , James Laudon , Jeffrey Adgate Dean , Kavya Srinivasa Setty , Omkar Pathak
IPC: G06F30/392 , G06N3/08 , G06F30/398
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
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