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公开(公告)号：US11556381B2
公开(公告)日：2023-01-17
申请号：US17738909
申请日：2022-05-06
申请人： Google LLC
发明人： Jeffrey Adgate Dean , Sudip Roy , Michael Acheson Isard , Aakanksha Chowdhery , Brennan Saeta , Chandramohan Amyangot Thekkath , Daniel William Hurt , Hyeontaek Lim , Laurent El Shafey , Parker Edward Schuh , Paul Ronald Barham , Ruoming Pang , Ryan Sepassi , Sanjay Ghemawat , Yonghui Wu
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing machine learning workloads, e.g., computations for training a neural network or computing an inference using a neural network, across multiple hardware accelerators. One of the systems comprises a plurality of accelerator islands, each hardware accelerator island comprising a respective plurality of hardware devices that include a plurality of hardware accelerators and a corresponding host for each of the plurality of hardware accelerators; and a respective scheduler for each of the accelerator islands that is configured to schedule workloads across the plurality of accelerators and corresponding hosts in the accelerator island, wherein the system is configured to: receive data representing a machine learning workload; and assign a respective portion of the machine learning workload to each of the plurality of accelerator islands for scheduling by the respective scheduler for the accelerator island.
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公开(公告)号：US20230118303A1
公开(公告)日：2023-04-20
申请号：US18082415
申请日：2022-12-15
申请人： Google LLC
发明人： Jeffrey Adgate Dean , Sudip Roy , Michael Acheson Isard , Aakanksha Chowdhery , Brennan Saeta , Chandramohan Amyangot Thekkath , Daniel William Hurt , Hyeontaek Lim , Laurent El Shafey , Parker Edward Schuh , Paul Ronald Barham , Ruoming Pang , Ryan Sepassi , Sanjay Ghemawat , Yonghui Wu
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing machine learning workloads, e.g., computations for training a neural network or computing an inference using a neural network, across multiple hardware accelerators. One of the systems comprises a plurality of accelerator islands, each hardware accelerator island comprising a respective plurality of hardware devices that include a plurality of hardware accelerators and a corresponding host for each of the plurality of hardware accelerators; and a respective scheduler for each of the accelerator islands that is configured to schedule workloads across the plurality of accelerators and corresponding hosts in the accelerator island, wherein the system is configured to: receive data representing a machine learning workload; and assign a respective portion of the machine learning workload to each of the plurality of accelerator islands for scheduling by the respective scheduler for the accelerator island.
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公开(公告)号：US12112198B2
公开(公告)日：2024-10-08
申请号：US18082415
申请日：2022-12-15
申请人： Google LLC
发明人： Jeffrey Adgate Dean , Sudip Roy , Michael Acheson Isard , Aakanksha Chowdhery , Brennan Saeta , Chandramohan Amyangot Thekkath , Daniel William Hurt , Hyeontaek Lim , Laurent El Shafey , Parker Edward Schuh , Paul Ronald Barham , Ruoming Pang , Ryan Sepassi , Sanjay Ghemawat , Yonghui Wu
CPC分类号： G06F9/4881 , G06N3/063 , G06N3/08
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing machine learning workloads, e.g., computations for training a neural network or computing an inference using a neural network, across multiple hardware accelerators. One of the systems comprises a plurality of accelerator islands, each hardware accelerator island comprising a respective plurality of hardware devices that include a plurality of hardware accelerators and a corresponding host for each of the plurality of hardware accelerators; and a respective scheduler for each of the accelerator islands that is configured to schedule workloads across the plurality of accelerators and corresponding hosts in the accelerator island, wherein the system is configured to: receive data representing a machine learning workload; and assign a respective portion of the machine learning workload to each of the plurality of accelerator islands for scheduling by the respective scheduler for the accelerator island.
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公开(公告)号：US20220357985A1
公开(公告)日：2022-11-10
申请号：US17738909
申请日：2022-05-06
申请人： Google LLC
发明人： Jeffrey Adgate Dean , Sudip Roy , Michael Acheson Isard , Aakanksha Chowdhery , Brennan Saeta , Chandramohan Amyangot Thekkath , Daniel William Hurt , Hyeontaek Lim , Laurent El Shafey , Parker Edward Schuh , Paul Ronald Barham , Ruoming Pang , Ryan Sepassi , Sanjay Ghemawat , Yonghui Wu
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing machine learning workloads, e.g., computations for training a neural network or computing an inference using a neural network, across multiple hardware accelerators. One of the systems comprises a plurality of accelerator islands, each hardware accelerator island comprising a respective plurality of hardware devices that include a plurality of hardware accelerators and a corresponding host for each of the plurality of hardware accelerators; and a respective scheduler for each of the accelerator islands that is configured to schedule workloads across the plurality of accelerators and corresponding hosts in the accelerator island, wherein the system is configured to: receive data representing a machine learning workload; and assign a respective portion of the machine learning workload to each of the plurality of accelerator islands for scheduling by the respective scheduler for the accelerator island.
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