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Microsoft Sessions at NVIDIA GTC

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KevinRaines
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Apr 08, 2021

 Microsoft Sessions at NVIDIA GTC

This year’s NVIDIA GTC event is certain not to disappoint. The big buzz around cloud-based NVIDIA GPUs is the introduction of deep learning and AI capabilities complementary to existing visualization, rendering, and gaming workflows. Having on-demand versatility by which GPUs can be consumed and transacted empowers greater productivity and efficiency with enhanced VDI/DaaS, real-time visualizations, and more immersive gaming & entertainment experiences.

 

This year we are sharing examples of some of the most versatile GPU-powered resources anywhere in the public cloud, with a clear understanding of maximum cost-for-performance metrics. We’re focusing on three main application use cases for GPUs:

  • Visualization, including 3D design rendering, remote rendering, and desktop virtualization
  • AI for machine learning, model training and inferencing
  • Edge Computing for hybrid scenarios, decoupled environments, and IoT device ecosystems

Microsoft Digital Sessions at NVIDIA GTC

Microsoft will be supporting the following pre-recorded sessions at GTC this year.

 

SESSION ID

TITLE

SPEAKER(S)

S32779

 

Azure: Empowering the World with High-Ambition AI and HPC

 

Girish Bablani, CVP, A and Ian Buck, VP Data Center, NVIDIA

S31060

Get to Solutioning: Strategy and Best Practices When Mapping Designs from Edge to Cloud

Paul DeCarlo Principal Cloud Advocate Microsoft

S31076

The Possibilities of Intelligence: How GPUs are Changing the Game across Industries

Rishabh Gaur Technical Architect Microsoft

S31141

Inferencing at Scale with Triton, Azure, and Microsoft Word Online

David Langworthy Architect Microsoft, Mahan Salehi Deep Learning Software PM NVIDIA, Emma Ning SPM Microsoft

S31330

Interactive Visualization of Large-Scale Super-Resolution Digital Core Samples in Azure

Kadri Umay WW CTO Process Manufacturing and Resources Microsoft Josephina Schembre-McCabe Digital Rock Technology R&D Specialist Chevron

S31582

Accelerating Large-Scale AI and HPC in the Cloud

Eddie Weill Data Scientist & Solutions Architect NVIDIA Jon Shelley HPC/AI Benchmarking Team, Principal PM Manager, Azure Compute Microsoft

S31594

Seamlessly Deploy Graphics-Intensive Geoscience Applications On-Prem and in the Cloud via Azure Stack HUB

Gaurang Candrakant Principal PM, Azure Edge + Platform Microsoft Shashank Panchangam Chief product Manager, Cloud services Halliburton

S31610

Accelerating AD/ADAS Development with Auto-Machine Learning + Auto-Labeling at Scale

Henry Bzeih CSO/CTO Automotive Microsoft Willy Kuo Chief Architect Linker Networks

S31614

Edge-Native Application Research using Azure Stack Hub by Carnegie Mellon University

Kirtana Venkatraman Program Manager 2 Microsoft James Blakley Living Edge Lab Associate Director Carnegie Mellon University Thomas Eiszler Senior Research Scientist Carnegie Mellon University

S31884

Latest Enhancements to CUDA Debugger IDEs

Julia Reid Program Manager 2 Microsoft Steve Ulrich Software Engineering Manager NVIDIA

S31873

Using Unreal Engine Anywhere from the Cloud to your HMD

Patrick Cesium xx Cesium Pete Rivera xx Microsoft Tim Woodard Senior Solutions Architect NVIDIA Sebastien Loze Epic Games Veronica Yip CloudXR Product Manager NVIDIA Sean Young Director of Global Business Development, Manufacturing NVIDIA

S32001

Deploy Compute and Software Resources to Run State-of-the-Art GPU-Supported AI/ML Applications in Azure Machine Learning with Just Two Commands

Accelerated Data Science

Krishna Anumalasetty Principal Program Manager Microsoft Manuel Reyes Gomez Developer Relations Manager NVIDIA

S32107

Building GPU-Accelerated Pipelines on Azure Synapse Analytics with RAPIDS

Rahul Potharaju Principal Big Data R&D Manager Microsoft Alexander Spiridonov Solution Architect NVIDIA

S31860

Introducing NVIDIA Nsight Perf SDK: A Graphics Profiling Toolbox

Avinash Baliga Software Engineering Manager NVIDIA Austin Kinross Senior Software Engineer Microsoft

S31644

Profiling PyTorch Models for NVIDIA GPUs

Geeta Chauhan PyTorch Partner Engineering Lead Facebook AI Gisle Dankel Software Engineer Facebook Maxim Lukiyanov Product Manager, PyTorch Profiler Microsoft

S32224

Accelerating Deep Learning Inference with OnnxRuntime-TensorRT

Steven Li Software Engineer Microsoft Kevin Chen NVIDIA Peter Pyun Principal Data Scientist NVIDIA

S32228

Build Immersive Mixed-Reality Experiences with Azure Remote Rendering.

Rachel Peters Senior Program Manager Azure Remote Rendering, Microsoft

S32240

ONNX Runtime: Accelerating PyTorch and TensorFlow Inferencing on Cloud and Edge

Peter Pyun Principal Data Scientist NVIDIA Emma Ning Senior Product Manager Microsoft

E32336

Microsoft Azure InfiniBand HPC Cloud User Experience and Best Practices

Gilad Shainer SVP Marketing, Networking NVIDIA Jithin Jose Senior Software Engineer, Microsoft Azure Microsoft

SS33079

Enterprise ready ML Model Training on NVIDIA GPUs across Hybrid Cloud, leveraging Kubernetes

Saurya Das Product Manager, Azure ML Microsoft

S31076

Bringing AI to the Edge

Rishabh Gaur Technical Architect Microsoft

S32184

Azure Live Video Analytics with Nvidia DeepStream

Avi Kewalramani Sr. Product Manager Microsoft

SS33161

Bringing Powerful Rendering and Graphics Visualization to Enterprises

Christiaan Brinkhoff, Principal Program Manager, Microsoft and Vijay Kanchanahalli Principal Program Manager, Microsoft

SS33165

Azure AI for Earth Planetary Computer​

Tom Augspurger​, Geospatial Infrastructure Engineer​, Microsoft

SS33166

Accelerating Biodiversity Surveys with AI​

Dan Morris, Principal Scientist, Microsoft

SS33167

Enabling Extreme I/O Workloads on Azure Machine Learning with Just-in-Time High-Performance File Systems​

Phil Tooley, HPC Software Engineer, NAG

S32032

Accelerating Azure Edge AI Vision Deployments 

Henry Jerez CTO, Microsoft Azure

 

NVIDIA DLI Training Powered by Azure

Microsoft is proud to host the NVIDIA DLI instructor-led online training covering AI, accelerated computing, and accelerated data science all powered on Microsoft Azure.

 

This year’s GTC event is shaping up to mark a major leap forward in how GPUs are utilized for modern application and service development workflows.

 

 

Updated Apr 09, 2021
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This year’s NVIDIA GTC event is certain not to disappoint. The big buzz around cloud-based NVIDIA GPUs is the introduction of deep learning and AI capabilities complementary to existing visualization, rendering, and gaming workflows. Having on-demand versatility by which GPUs can be consumed and transacted empowers greater productivity and efficiency with enhanced VDI/DaaS, real-time visualizations, and more immersive gaming & entertainment experiences.

","body":"

 Microsoft Sessions at NVIDIA GTC

\n

This year’s NVIDIA GTC event is certain not to disappoint. The big buzz around cloud-based NVIDIA GPUs is the introduction of deep learning and AI capabilities complementary to existing visualization, rendering, and gaming workflows. Having on-demand versatility by which GPUs can be consumed and transacted empowers greater productivity and efficiency with enhanced VDI/DaaS, real-time visualizations, and more immersive gaming & entertainment experiences.

\n

 

\n

This year we are sharing examples of some of the most versatile GPU-powered resources anywhere in the public cloud, with a clear understanding of maximum cost-for-performance metrics. We’re focusing on three main application use cases for GPUs:

\n\n

Microsoft Digital Sessions at NVIDIA GTC

\n

Microsoft will be supporting the following pre-recorded sessions at GTC this year.

\n

 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

SESSION ID

\n		\n

TITLE

\n		\n

SPEAKER(S)

\n
\n

S32779

\n

 

\n		\n

Azure: Empowering the World with High-Ambition AI and HPC

\n

 

\n		\n

Girish Bablani, CVP, A and Ian Buck, VP Data Center, NVIDIA

\n
\n

S31060

\n		\n

Get to Solutioning: Strategy and Best Practices When Mapping Designs from Edge to Cloud

\n		\n

Paul DeCarlo Principal Cloud Advocate Microsoft

\n
\n

S31076

\n		\n

The Possibilities of Intelligence: How GPUs are Changing the Game across Industries

\n		\n

Rishabh Gaur Technical Architect Microsoft

\n
\n

S31141

\n		\n

Inferencing at Scale with Triton, Azure, and Microsoft Word Online

\n		\n

David Langworthy Architect Microsoft, Mahan Salehi Deep Learning Software PM NVIDIA, Emma Ning SPM Microsoft

\n
\n

S31330

\n		\n

Interactive Visualization of Large-Scale Super-Resolution Digital Core Samples in Azure

\n		\n

Kadri Umay WW CTO Process Manufacturing and Resources Microsoft Josephina Schembre-McCabe Digital Rock Technology R&D Specialist Chevron

\n
\n

S31582

\n		\n

Accelerating Large-Scale AI and HPC in the Cloud

\n		\n

Eddie Weill Data Scientist & Solutions Architect NVIDIA Jon Shelley HPC/AI Benchmarking Team, Principal PM Manager, Azure Compute Microsoft

\n
\n

S31594

\n		\n

Seamlessly Deploy Graphics-Intensive Geoscience Applications On-Prem and in the Cloud via Azure Stack HUB

\n		\n

Gaurang Candrakant Principal PM, Azure Edge + Platform Microsoft Shashank Panchangam Chief product Manager, Cloud services Halliburton

\n
\n

S31610

\n		\n

Accelerating AD/ADAS Development with Auto-Machine Learning + Auto-Labeling at Scale

\n		\n

Henry Bzeih CSO/CTO Automotive Microsoft Willy Kuo Chief Architect Linker Networks

\n
\n

S31614

\n		\n

Edge-Native Application Research using Azure Stack Hub by Carnegie Mellon University

\n		\n

Kirtana Venkatraman Program Manager 2 Microsoft James Blakley Living Edge Lab Associate Director Carnegie Mellon University Thomas Eiszler Senior Research Scientist Carnegie Mellon University

\n
\n

S31884

\n		\n

Latest Enhancements to CUDA Debugger IDEs

\n		\n

Julia Reid Program Manager 2 Microsoft Steve Ulrich Software Engineering Manager NVIDIA

\n
\n

S31873

\n		\n

Using Unreal Engine Anywhere from the Cloud to your HMD

\n		\n

Patrick Cesium xx Cesium Pete Rivera xx Microsoft Tim Woodard Senior Solutions Architect NVIDIA Sebastien Loze Epic Games Veronica Yip CloudXR Product Manager NVIDIA Sean Young Director of Global Business Development, Manufacturing NVIDIA

\n
\n

S32001

\n		\n

Deploy Compute and Software Resources to Run State-of-the-Art GPU-Supported AI/ML Applications in Azure Machine Learning with Just Two Commands

\n		\n

Accelerated Data Science

\n

Krishna Anumalasetty Principal Program Manager Microsoft Manuel Reyes Gomez Developer Relations Manager NVIDIA

\n
\n

S32107

\n		\n

Building GPU-Accelerated Pipelines on Azure Synapse Analytics with RAPIDS

\n		\n

Rahul Potharaju Principal Big Data R&D Manager Microsoft Alexander Spiridonov Solution Architect NVIDIA

\n
\n

S31860

\n		\n

Introducing NVIDIA Nsight Perf SDK: A Graphics Profiling Toolbox

\n		\n

Avinash Baliga Software Engineering Manager NVIDIA Austin Kinross Senior Software Engineer Microsoft

\n
\n

S31644

\n		\n

Profiling PyTorch Models for NVIDIA GPUs

\n		\n

Geeta Chauhan PyTorch Partner Engineering Lead Facebook AI Gisle Dankel Software Engineer Facebook Maxim Lukiyanov Product Manager, PyTorch Profiler Microsoft

\n
\n

S32224

\n		\n

Accelerating Deep Learning Inference with OnnxRuntime-TensorRT

\n		\n

Steven Li Software Engineer Microsoft Kevin Chen NVIDIA Peter Pyun Principal Data Scientist NVIDIA

\n
\n

S32228

\n		\n

Build Immersive Mixed-Reality Experiences with Azure Remote Rendering.

\n		\n

Rachel Peters Senior Program Manager Azure Remote Rendering, Microsoft

\n
\n

S32240

\n		\n

ONNX Runtime: Accelerating PyTorch and TensorFlow Inferencing on Cloud and Edge

\n		\n

Peter Pyun Principal Data Scientist NVIDIA Emma Ning Senior Product Manager Microsoft

\n
\n

E32336

\n		\n

Microsoft Azure InfiniBand HPC Cloud User Experience and Best Practices

\n		\n

Gilad Shainer SVP Marketing, Networking NVIDIA Jithin Jose Senior Software Engineer, Microsoft Azure Microsoft

\n
\n

SS33079

\n		\n

Enterprise ready ML Model Training on NVIDIA GPUs across Hybrid Cloud, leveraging Kubernetes

\n		\n

Saurya Das Product Manager, Azure ML Microsoft

\n
\n

S31076

\n		\n

Bringing AI to the Edge

\n		\n

Rishabh Gaur Technical Architect Microsoft

\n
\n

S32184

\n		\n

Azure Live Video Analytics with Nvidia DeepStream

\n		\n

Avi Kewalramani Sr. Product Manager Microsoft

\n
\n

SS33161

\n		\n

Bringing Powerful Rendering and Graphics Visualization to Enterprises

\n		\n

Christiaan Brinkhoff, Principal Program Manager, Microsoft and Vijay Kanchanahalli Principal Program Manager, Microsoft

\n
\n

SS33165

\n		\n

Azure AI for Earth Planetary Computer​

\n		\n

Tom Augspurger​, Geospatial Infrastructure Engineer​, Microsoft

\n
\n

SS33166

\n		\n

Accelerating Biodiversity Surveys with AI​

\n		\n

Dan Morris, Principal Scientist, Microsoft

\n
\n

SS33167

\n		\n

Enabling Extreme I/O Workloads on Azure Machine Learning with Just-in-Time High-Performance File Systems​

\n		\n

Phil Tooley, HPC Software Engineer, NAG

\n
\n

S32032

\n		\n

Accelerating Azure Edge AI Vision Deployments 

\n		\n

Henry Jerez CTO, Microsoft Azure

\n
\n

 

\n

NVIDIA DLI Training Powered by Azure

\n

Microsoft is proud to host the NVIDIA DLI instructor-led online training covering AI, accelerated computing, and accelerated data science all powered on Microsoft Azure.

\n

 

\n

This year’s GTC event is shaping up to mark a major leap forward in how GPUs are utilized for modern application and service development workflows.

\n

 

\n

 

","body@stringLength":"19698","rawBody":"

 Microsoft Sessions at NVIDIA GTC

\n

This year’s NVIDIA GTC event is certain not to disappoint. The big buzz around cloud-based NVIDIA GPUs is the introduction of deep learning and AI capabilities complementary to existing visualization, rendering, and gaming workflows. Having on-demand versatility by which GPUs can be consumed and transacted empowers greater productivity and efficiency with enhanced VDI/DaaS, real-time visualizations, and more immersive gaming & entertainment experiences.

\n

 

\n

This year we are sharing examples of some of the most versatile GPU-powered resources anywhere in the public cloud, with a clear understanding of maximum cost-for-performance metrics. We’re focusing on three main application use cases for GPUs:

\n\n

Microsoft Digital Sessions at NVIDIA GTC

\n

Microsoft will be supporting the following pre-recorded sessions at GTC this year.

\n

 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

SESSION ID

\n		\n

TITLE

\n		\n

SPEAKER(S)

\n
\n

S32779

\n

 

\n		\n

Azure: Empowering the World with High-Ambition AI and HPC

\n

 

\n		\n

Girish Bablani, CVP, A and Ian Buck, VP Data Center, NVIDIA

\n
\n

S31060

\n		\n

Get to Solutioning: Strategy and Best Practices When Mapping Designs from Edge to Cloud

\n		\n

Paul DeCarlo Principal Cloud Advocate Microsoft

\n
\n

S31076

\n		\n

The Possibilities of Intelligence: How GPUs are Changing the Game across Industries

\n		\n

Rishabh Gaur Technical Architect Microsoft

\n
\n

S31141

\n		\n

Inferencing at Scale with Triton, Azure, and Microsoft Word Online

\n		\n

David Langworthy Architect Microsoft, Mahan Salehi Deep Learning Software PM NVIDIA, Emma Ning SPM Microsoft

\n
\n

S31330

\n		\n

Interactive Visualization of Large-Scale Super-Resolution Digital Core Samples in Azure

\n		\n

Kadri Umay WW CTO Process Manufacturing and Resources Microsoft Josephina Schembre-McCabe Digital Rock Technology R&D Specialist Chevron

\n
\n

S31582

\n		\n

Accelerating Large-Scale AI and HPC in the Cloud

\n		\n

Eddie Weill Data Scientist & Solutions Architect NVIDIA Jon Shelley HPC/AI Benchmarking Team, Principal PM Manager, Azure Compute Microsoft

\n
\n

S31594

\n		\n

Seamlessly Deploy Graphics-Intensive Geoscience Applications On-Prem and in the Cloud via Azure Stack HUB

\n		\n

Gaurang Candrakant Principal PM, Azure Edge + Platform Microsoft Shashank Panchangam Chief product Manager, Cloud services Halliburton

\n
\n

S31610

\n		\n

Accelerating AD/ADAS Development with Auto-Machine Learning + Auto-Labeling at Scale

\n		\n

Henry Bzeih CSO/CTO Automotive Microsoft Willy Kuo Chief Architect Linker Networks

\n
\n

S31614

\n		\n

Edge-Native Application Research using Azure Stack Hub by Carnegie Mellon University

\n		\n

Kirtana Venkatraman Program Manager 2 Microsoft James Blakley Living Edge Lab Associate Director Carnegie Mellon University Thomas Eiszler Senior Research Scientist Carnegie Mellon University

\n
\n

S31884

\n		\n

Latest Enhancements to CUDA Debugger IDEs

\n		\n

Julia Reid Program Manager 2 Microsoft Steve Ulrich Software Engineering Manager NVIDIA

\n
\n

S31873

\n		\n

Using Unreal Engine Anywhere from the Cloud to your HMD

\n		\n

Patrick Cesium xx Cesium Pete Rivera xx Microsoft Tim Woodard Senior Solutions Architect NVIDIA Sebastien Loze Epic Games Veronica Yip CloudXR Product Manager NVIDIA Sean Young Director of Global Business Development, Manufacturing NVIDIA

\n
\n

S32001

\n		\n

Deploy Compute and Software Resources to Run State-of-the-Art GPU-Supported AI/ML Applications in Azure Machine Learning with Just Two Commands

\n		\n

Accelerated Data Science

\n

Krishna Anumalasetty Principal Program Manager Microsoft Manuel Reyes Gomez Developer Relations Manager NVIDIA

\n
\n

S32107

\n		\n

Building GPU-Accelerated Pipelines on Azure Synapse Analytics with RAPIDS

\n		\n

Rahul Potharaju Principal Big Data R&D Manager Microsoft Alexander Spiridonov Solution Architect NVIDIA

\n
\n

S31860

\n		\n

Introducing NVIDIA Nsight Perf SDK: A Graphics Profiling Toolbox

\n		\n

Avinash Baliga Software Engineering Manager NVIDIA Austin Kinross Senior Software Engineer Microsoft

\n
\n

S31644

\n		\n

Profiling PyTorch Models for NVIDIA GPUs

\n		\n

Geeta Chauhan PyTorch Partner Engineering Lead Facebook AI Gisle Dankel Software Engineer Facebook Maxim Lukiyanov Product Manager, PyTorch Profiler Microsoft

\n
\n

S32224

\n		\n

Accelerating Deep Learning Inference with OnnxRuntime-TensorRT

\n		\n

Steven Li Software Engineer Microsoft Kevin Chen NVIDIA Peter Pyun Principal Data Scientist NVIDIA

\n
\n

S32228

\n		\n

Build Immersive Mixed-Reality Experiences with Azure Remote Rendering.

\n		\n

Rachel Peters Senior Program Manager Azure Remote Rendering, Microsoft

\n
\n

S32240

\n		\n

ONNX Runtime: Accelerating PyTorch and TensorFlow Inferencing on Cloud and Edge

\n		\n

Peter Pyun Principal Data Scientist NVIDIA Emma Ning Senior Product Manager Microsoft

\n
\n

E32336

\n		\n

Microsoft Azure InfiniBand HPC Cloud User Experience and Best Practices

\n		\n

Gilad Shainer SVP Marketing, Networking NVIDIA Jithin Jose Senior Software Engineer, Microsoft Azure Microsoft

\n
\n

SS33079

\n		\n

Enterprise ready ML Model Training on NVIDIA GPUs across Hybrid Cloud, leveraging Kubernetes

\n		\n

Saurya Das Product Manager, Azure ML Microsoft

\n
\n

S31076

\n		\n

Bringing AI to the Edge

\n		\n

Rishabh Gaur Technical Architect Microsoft

\n
\n

S32184

\n		\n

Azure Live Video Analytics with Nvidia DeepStream

\n		\n

Avi Kewalramani Sr. Product Manager Microsoft

\n
\n

SS33161

\n		\n

Bringing Powerful Rendering and Graphics Visualization to Enterprises

\n		\n

Christiaan Brinkhoff, Principal Program Manager, Microsoft and Vijay Kanchanahalli Principal Program Manager, Microsoft

\n
\n

SS33165

\n		\n

Azure AI for Earth Planetary Computer​

\n		\n

Tom Augspurger​, Geospatial Infrastructure Engineer​, Microsoft

\n
\n

SS33166

\n		\n

Accelerating Biodiversity Surveys with AI​

\n		\n

Dan Morris, Principal Scientist, Microsoft

\n
\n

SS33167

\n		\n

Enabling Extreme I/O Workloads on Azure Machine Learning with Just-in-Time High-Performance File Systems​

\n		\n

Phil Tooley, HPC Software Engineer, NAG

\n
\n

S32032

\n		\n

Accelerating Azure Edge AI Vision Deployments 

\n		\n

Henry Jerez CTO, Microsoft Azure

\n
\n

 

\n

NVIDIA DLI Training Powered by Azure

\n

Microsoft is proud to host the NVIDIA DLI instructor-led online training covering AI, accelerated computing, and accelerated data science all powered on Microsoft Azure.

\n

 

\n

This year’s GTC event is shaping up to mark a major leap forward in how GPUs are utilized for modern application and service development workflows.

\n

 

\n

 

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