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公开(公告)号：US11960936B2
公开(公告)日：2024-04-16
申请号：US17150285
申请日：2021-01-15
Applicant: Google LLC
Inventor： David Lo , Liqun Cheng , Parthasarathy Ranganathan , Sundar Jayakumar Dev
CPC classification number: G06F9/5027 , G06N20/00
Abstract: The subject matter described herein provides systems and techniques to address the challenges of growing hardware and workload heterogeneity using a Warehouse-Scale Computer (WSC) design that improves the efficiency and utilization of WSCs. The WSC design may include an abstraction layer and an efficiency layer in the software stack of the WSC. The abstraction layer and the efficiency layer may be designed to improve job scheduling, simplify resource management, and drive hardware-software co-optimization using machine learning techniques and automation in order to customize the WSC for applications at scale. The abstraction layer may embrace platform/hardware and workload diversity through greater coordination between hardware and higher layers of the WSC software stack in the WSC design. The efficiency layer may employ machine learning techniques at scale to realize hardware/software co-optimizations as a part of the autonomous WSC design.
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公开(公告)号：US10908964B2
公开(公告)日：2021-02-02
申请号：US16198583
申请日：2018-11-21
Applicant: Google LLC
Inventor： Liqun Cheng , Rama Krishna Govindaraju , Haishan Zhu , David Lo , Parthasarathy Ranganathan , Nishant Patil
Abstract: Methods, systems, and computer storage media storing instructions for managing processing system efficiency. One of the methods includes obtaining data splitting a plurality of general-purpose processing units in a processing system into a high-priority domain and a low-priority domain, wherein the general-purpose processing units in the high-priority domain are assigned to perform one or more tasks comprising one or more high-priority tasks, and the general-purpose processing units in the low-priority domain are assigned to perform one or more low-priority tasks; and during runtime of the processing system, obtaining memory usage measurements that characterize usage of system memory by the high-priority domain and the low-priority domain; and adjusting, based on the memory usage measurements, a configuration of (i) the high-priority domain, (ii) the low-priority domain, or (iii) both to adjust utilization of the system memory by the general-purpose processing units.
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Patent Agency Ranking
公开(公告)号：US11704158B2
公开(公告)日：2023-07-18
申请号：US17162682
申请日：2021-01-29
Applicant: Google LLC
Inventor： Liqun Cheng , Rama Krishna Govindaraju , Haishan Zhu , David Lo , Parthasarathy Ranganathan , Nishant Patil
CPC classification number: G06F9/5038 , G06F9/4881 , G06F9/505 , G06F9/5016 , G06F9/5061 , G06F9/5083 , G06N20/00
Abstract: Methods, systems, and computer storage media storing instructions for managing processing system efficiency. One of the methods includes obtaining data splitting a plurality of general-purpose processing units in a processing system into a high-priority domain and a low-priority domain, wherein the general-purpose processing units in the high-priority domain are assigned to perform one or more tasks comprising one or more high-priority tasks, and the general-purpose processing units in the low-priority domain are assigned to perform one or more low-priority tasks; and during runtime of the processing system, obtaining memory usage measurements that characterize usage of system memory by the high-priority domain and the low-priority domain; and adjusting, based on the memory usage measurements, a configuration of (i) the high-priority domain, (ii) the low-priority domain, or (iii) both to adjust utilization of the system memory by the general-purpose processing units.
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公开(公告)号：US20210224129A1
公开(公告)日：2021-07-22
申请号：US17162682
申请日：2021-01-29
Applicant: Google LLC
Inventor： Liqun Cheng , Rama Krishna Govindaraju , Haishan Zhu , David Lo , Parthasarathy Ranganathan , Nishant Patil
Abstract: Methods, systems, and computer storage media storing instructions for managing processing system efficiency. One of the methods includes obtaining data splitting a plurality of general-purpose processing units in a processing system into a high-priority domain and a low-priority domain, wherein the general-purpose processing units in the high-priority domain are assigned to perform one or more tasks comprising one or more high-priority tasks, and the general-purpose processing units in the low-priority domain are assigned to perform one or more low-priority tasks; and during runtime of the processing system, obtaining memory usage measurements that characterize usage of system memory by the high-priority domain and the low-priority domain; and adjusting, based on the memory usage measurements, a configuration of (i) the high-priority domain, (ii) the low-priority domain, or (iii) both to adjust utilization of the system memory by the general-purpose processing units.
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公开(公告)号：US20200027155A1
公开(公告)日：2020-01-23
申请号：US16487648
申请日：2018-03-27
Applicant: Google LLC
Inventor： David Frakes , David Lo , Eric Aboussouan , Mohamed Haitham Musa Babiker , Karl Patrick Lawrence , Roshanbir Bhatia , Mark Nelson
Abstract: Systems and methods for visualizing garment fit are provided. In one embodiment, the method can include obtaining garment data descriptive of a garment and body data descriptive of a body. The method can further include simulating a garment deformation of the garment due to contact from the body, and determining a simulating a body deformation of the body due to contact from the garment. The method can further include providing a visualization of the garment on the body for display to a user, the visualization visualizing the garment deformation and the body deformation.
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公开(公告)号：US20190155658A1
公开(公告)日：2019-05-23
申请号：US16198583
申请日：2018-11-21
Applicant: Google LLC
Inventor： Liqun Cheng , Rama Krishna Govindaraju , Haishan Zhu , David Lo , Parthasarathy Ranganathan , Nishant Patil
Abstract: Methods, systems, and computer storage media storing instructions for managing processing system efficiency. One of the methods includes obtaining data splitting a plurality of general-purpose processing units in a processing system into a high-priority domain and a low-priority domain, wherein the general-purpose processing units in the high-priority domain are assigned to perform one or more tasks comprising one or more high-priority tasks, and the general-purpose processing units in the low-priority domain are assigned to perform one or more low-priority tasks; and during runtime of the processing system, obtaining memory usage measurements that characterize usage of system memory by the high-priority domain and the low-priority domain; and adjusting, based on the memory usage measurements, a configuration of (i) the high-priority domain, (ii) the low-priority domain, or (iii) both to adjust utilization of the system memory by the general-purpose processing units.
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公开(公告)号：US20220229698A1
公开(公告)日：2022-07-21
申请号：US17150285
申请日：2021-01-15
Applicant: Google LLC
Inventor： David Lo , Liqun Cheng , Parthasarathy Ranganathan , Sundar Jayakumar Dev
Abstract: The subject matter described herein provides systems and techniques to address the challenges of growing hardware and workload heterogeneity using a Warehouse-Scale Computer (WSC) design that improves the efficiency and utilization of WSCs. The WSC design may include an abstraction layer and an efficiency layer in the software stack of the WSC. The abstraction layer and the efficiency layer may be designed to improve job scheduling, simplify resource management, and drive hardware-software co-optimization using machine learning techniques and automation in order to customize the WSC for applications at scale. The abstraction layer may embrace platform/hardware and workload diversity through greater coordination between hardware and higher layers of the WSC software stack in the WSC design. The efficiency layer may employ machine learning techniques at scale to realize hardware/software co-optimizations as a part of the autonomous WSC design.
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