Jetson Platform Services

What is Jetson Platform Services?

NVIDIA Jetson Platform Services, an integral component of NVIDIA JetPack™ SDK, gives you a collection of powerful cloud-native microservices and building blocks to build powerful vision AI applications for the edge powered by NVIDIA Jetson™. Jetson Platform Services simplifies development, deployment and management of Edge AI applications for NVIDIA Jetson by providing a modular and extensible architecture for developers to distill large complex applications into smaller modular microservice with APIs to integrate into other apps and services.

Elevate your application by seamlessly integrating generative AI capabilities and future-proof your solutions through a sophisticated blend of microservices, providing an API-driven, modular, and highly extensible framework.

This latest release of NVIDIA Jetson Platform Services includes:

Reference workflows for: AI-NVR, Zero-shot Detection with Grounding-DINO, and video summarization and Q&A using Vision Language Model (VLM)
15+ services, including generative AI services, foundation services, and more
Streaming generative AI services for vision language model and zero-shot detection with APIs for dynamic prompting and stream update
DeepStream-based AI perception service for object detection and tracking with APIs for stream update
Media management and storage service with support for streaming protocol such as RTSP and WebRTC
Core foundation services like API Gateway, monitoring, and system bus

How to Get Started?

Hardware Requirements:

Jetson Orin AGX devkit or
Jetson Orin NX 16GB or 8GB devkit (self built) with 128GB(min) NVMe drive or
Jetson Orin Nano 8GB devkit with 128GB(min) NVMe drive or
Jetson Orin Nano Super
Partner (ODM) device with one of above
Ubuntu 20.04 or 22.04 Desktop/Laptop
USB-C flashing cable
Monitor, Keyboard, Mouse

For full requirement and hardware setup, refer to the Preparation and Hardware Setup in the Quick Start Guide.

Software Requirements:

JetPack 6.2/Jetson Linux 36.4.3
Jetson Platform services 2.0

The only requirement to use Jetson Platform Services 2.0 is JetPack 6.2/Jetson Linux 36.4.3 (or JetPack 6.1/Jetson Linux 36.4.0). For full instructions on flashing the device with JetPack 6.2, please refer to Software Setup in Quick Start Guide. Follow instructions all the way down to Installing Jetson Platform Services.

Download and Extract Bundle:
\nDownload the reference workflow and resource bundle from this page as a starting point. This bundle will include the resources required to run the reference workflows for the Hello World example, AI-NVR, Zero-shot Detection and video summarization and Q&A.

Run Hello World Example:
\nContinue following the Quick Start Guide through the Setup steps and Hello World example to get familiar with Jetson Platform Services.

This Hello World example will show to run an Intelligent Video Analytics application that will uses RTSP streams generated by NVStreamer, draw trip wires and regions of interest with the Video Storage Toolkit and automatically inference the streams with DeepStream and generate analytic data.

Advanced Workflows:
\nTo continue with the more advanced workflows for AI-NVR and generative AI also found in this resource bundle, view the pages below:

Package Content:\nThis NGC resource contains several tar files.

The following packages contain docker compose and configuration files needed to run each workflow or microservice.

ai_nvr-2.0.1.tar.gz
zero_shot_detection-2.0.0.tar.gz
vlm-2.0.0.tar.gz
nvstreamer-2.0.0.tar.gz

Additionally some starter resources are also included such as sample videos.

ai-nvr-app-android-2.0.0.tar.gz
sample_1080p_h264.mp4

Navigating all the resources on NGC

All the resources are provided on NGC.

\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

tr:nth-child(odd)]:bg-surface-sunken\">

Category	Name	Description
Resources	Jetson Platform Services Reference Workflow & Resources	Starting resources for Jetson Platform Services. Includes sample worfklows, videos and scripts.
Container	deepstream	AI perception service with pre-built DeepStream pipeline and PeopleNet model for People Detection
Container	zero_shot_detection_infer	Zero Shot Detection AI service that performs open vocabulary detection on live streams and is controllable through REST APIs.
Container	vlm_infer	Vision Language Model (VLM) AI service that allows VLM inference on live stream with custom user prompts and alerts controllable through REST APIs.
Container	vlm_summarization	Video summarization service offers an accurate, generalizable technique based on natural language interfaces for performing video summarization on stored videos.
Container	jps-gdino	Grounding DINO service that supports open vocabulary object detection for zero-shot object detection.
Resources	Jetson Platform Services OSS Sources	Package that includes all third part OSS source code and licenses used across all Jetson Platform Services.
Container	ialpha-ingress-arm64v8	A reverse proxy that forwards incoming API requests to the appropriate microservice
Container	its-monitoring	Used to monitor, persist, and visualize edge device status
Container	jps-metric-exporter	Used to monitor system metrics and export to Promtheus for tracking
Container	vst:x_aarch64	Video Storage Toolkit microservice that enables discovery, storage and streaming of video sources
Container	vst:x_aarch64	NVStreamer container built for Jetson. Used to serve video files as RTSP streams.
Container	vst:x_x86_64	NVStreamer container built for x86. Can be used on x86 device to serve video files as RTSP streams.
Container	emdx-analytics	Analytics service to create count analytics like line-crossing, Region of Interest (ROIs) and Field of View (FOV)
Container	emdx-analytics-web-api	Provides APIs to interact with the Analytics service
Container	sdr	Microservice to dynamically add & register streams to Deepstream, Analytic and Generative AI conatiners
Container	sdr-reprovision-controller	Microservice to ensure SDR and VST stream lists are in sync
Container	sdr-alertmanager-controller	A SDR sidecar container to process alerts sent by monitoring via Alertmanager
Container	sdr-proxy-controller	An SDR sidecar container to convert request formatting to/from versions compatible with the main SDR container

Developer Resources

Documentation - Jetson Platform Services
\nDocumentation - Quick Start Guide
\nBlog - Bringing Generative AI to the Edge
\nBlog - Build Vision AI Applications with APIs
\nTechnical Whitepaper on Microservices for Jetson
\nWebinar Part 1 - Accelerate Edge AI Development With Metropolis APIs and Microservices on Jetson
\nWebinar Part 2 - How to Build With Metropolis Microservices for Jetson
\nLearn more about Metropolis Microservices

License

By downloading or using the software and materials, you agree to the License Agreement for Jetson Platform Services

","resourceVersions",[241,242,243,244],"resourceVersionsTotal","hasMoreVersions","versionMetadata",{"_224":29,"_225":-5,"_53":121,"_118":-5,"_122":226,"_124":-5,"_227":141,"_129":140,"_126":35,"_228":-5,"_125":35,"_229":-5,"_230":35,"_231":232,"_233":35,"_234":232,"_235":35,"_236":232,"_237":35,"_238":232,"_239":35,"_127":240},"versionNotFound","isLoggedIn","latestVersionPath","/orgs/nvidia/jps/resources/reference-workflow-and-resources/-","-","imageReference","cliDownloadCommand","ngc registry resource download-version nvidia/jps/reference-workflow-and-resources:2.0.1","helmFetchCommand","viewAllVersionsPath","/orgs/nvidia/jps/resources/reference-workflow-and-resources/-/version-history","accessCheckResult",{"_223":92},"hasRelatedCollections","context",{"_219":220,"_221":222},1783955617276,[],[],[212,213,214,215,216,217,218],{"_49":64,"_51":75,"_53":66,"_55":67,"_57":76,"_59":60},{"_49":64,"_51":73,"_53":160,"_55":-5,"_57":-5,"_59":60},{"_49":64,"_51":71,"_53":66,"_55":67,"_57":72,"_59":60},{"_49":64,"_51":69,"_53":66,"_55":67,"_57":70,"_59":60},{"_49":64,"_51":65,"_53":66,"_55":67,"_57":68,"_59":60},{"_49":61,"_51":62,"_53":54,"_55":56,"_57":63,"_59":60},{"_49":50,"_51":52,"_53":54,"_55":56,"_57":58,"_59":60},"orgName","nvidia","teamName","jps","allowed","versionId","description",["D",1736980940225],"totalSizeInBytes","malwareScanStatus","releaseNotes","hasReleaseNotes","setup","","hasSetup","quickStartGuide","hasQuickStartGuide","advanced","hasAdvanced","performance","hasPerformance",[],{"_87":196,"_117":248,"_118":-5,"_126":35,"_125":35,"_127":247,"_230":35},{"_87":29,"_117":29,"_118":-5,"_126":35,"_125":35,"_127":247,"_230":35},{"_87":136,"_117":136,"_118":-5,"_126":35,"_125":35,"_127":246,"_230":35},{"_87":116,"_117":116,"_118":-5,"_126":35,"_125":35,"_127":245,"_230":35},[],[],[],"Latest (2.0.1)","nvidia/jps/reference-workflow-and-resources","key","nvidia/jps/resources/reference-workflow-and-resources","resourceId","reference-workflow-and-resources","shortDescription","Jetson Platform Services Reference Workflow & Resources","# Jetson Platform Services\n\n## What is Jetson Platform Services?\nNVIDIA Jetson Platform Services, an integral component of NVIDIA JetPack™ SDK, gives you a collection of powerful cloud-native microservices and building blocks to build powerful vision AI applications for the edge powered by NVIDIA Jetson™. Jetson Platform Services simplifies development, deployment and management of Edge AI applications for NVIDIA Jetson by providing a modular and extensible architecture for developers to distill large complex applications into smaller modular microservice with APIs to integrate into other apps and services.\n\nElevate your application by seamlessly integrating generative AI capabilities and future-proof your solutions through a sophisticated blend of microservices, providing an API-driven, modular, and highly extensible framework. \n\nThis latest release of NVIDIA Jetson Platform Services includes: \n\n- Reference workflows for: AI-NVR, Zero-shot Detection with Grounding-DINO, and video summarization and Q&A using Vision Language Model (VLM)\n- 15+ services, including generative AI services, foundation services, and more\n- Streaming generative AI services for vision language model and zero-shot detection with APIs for dynamic prompting and stream update\n- DeepStream-based AI perception service for object detection and tracking with APIs for stream update\n- Media management and storage service with support for streaming protocol such as RTSP and WebRTC\n- Core foundation services like API Gateway, monitoring, and system bus\n\n## How to Get Started?\n**Hardware Requirements:**\n- Jetson Orin AGX devkit or\n- Jetson Orin NX 16GB or 8GB devkit (self built) with 128GB(min) NVMe drive or\n- Jetson Orin Nano 8GB devkit with 128GB(min) NVMe drive or\n- Jetson Orin Nano Super\n- Partner (ODM) device with one of above\n- Ubuntu 20.04 or 22.04 Desktop/Laptop\n- USB-C flashing cable\n- Monitor, Keyboard, Mouse\n\nFor full requirement and hardware setup, refer to the [Preparation and Hardware Setup](https://docs.nvidia.com/jetson/jps/setup/quick-start.html#preparation) in the Quick Start Guide. \n\n\n**Software Requirements:**\n- JetPack 6.2/Jetson Linux 36.4.3\n- Jetson Platform services 2.0\n\nThe only requirement to use Jetson Platform Services 2.0 is JetPack 6.2/Jetson Linux 36.4.3 (or JetPack 6.1/Jetson Linux 36.4.0). For full instructions on flashing the device with JetPack 6.2, please refer to [Software Setup](https://docs.nvidia.com/jetson/jps/setup/quick-start.html#software-setup) in Quick Start Guide. Follow instructions all the way down to Installing Jetson Platform Services. \n\n**Download and Extract Bundle:** \\\nDownload the reference workflow and resource bundle from this page as a starting point. This bundle will include the resources required to run the reference workflows for the Hello World example, AI-NVR, Zero-shot Detection and video summarization and Q&A. \n\n**Run Hello World Example:** \\\nContinue following the Quick Start Guide through the [Setup](https://docs.nvidia.com/jetson/jps/setup/quick-start.html#setups) steps and [Hello World example](https://docs.nvidia.com/jetson/jps/setup/quick-start.html#running-hello-world) to get familiar with Jetson Platform Services. \n\nThis Hello World example will show to run an Intelligent Video Analytics application that will uses RTSP streams generated by NVStreamer, draw trip wires and regions of interest with the Video Storage Toolkit and automatically inference the streams with DeepStream and generate analytic data. \n\n**Advanced Workflows:** \\\nTo continue with the more advanced workflows for AI-NVR and generative AI also found in this resource bundle, view the pages below:\n- [AI-NVR](https://docs.nvidia.com/jetson/jps/setup/ai-nvr.html)\n- [Zero Shot Detection](https://docs.nvidia.com/jetson/jps/workflows/zero_shot_detection_workflow.html)\n- [VLM](https://docs.nvidia.com/jetson/jps/workflows/vlm_workflow.html)\n\n**Package Content:**\nThis NGC resource contains several tar files. \n\nThe following packages contain docker compose and configuration files needed to run each workflow or microservice.\n- ai_nvr-2.0.1.tar.gz\n- zero_shot_detection-2.0.0.tar.gz\n- vlm-2.0.0.tar.gz\n- nvstreamer-2.0.0.tar.gz\n\nAdditionally some starter resources are also included such as sample videos. \n- ai-nvr-app-android-2.0.0.tar.gz\n- sample_1080p_h264.mp4\n\n## Navigating all the resources on NGC\nAll the resources are provided on NGC. \n\n|Category |Name |Description |\n|----------|--------------------------|------------------------------------------------------------------|\n|Resources |Jetson Platform Services Reference Workflow & Resources | Starting resources for Jetson Platform Services. Includes sample worfklows, videos and scripts.|\n|Container |deepstream |AI perception service with pre-built DeepStream pipeline and PeopleNet model for People Detection |\n|Container | zero_shot_detection_infer | Zero Shot Detection AI service that performs open vocabulary detection on live streams and is controllable through REST APIs. |\n|Container | vlm_infer | Vision Language Model (VLM) AI service that allows VLM inference on live stream with custom user prompts and alerts controllable through REST APIs. |\n|Container | vlm_summarization | Video summarization service offers an accurate, generalizable technique based on natural language interfaces for performing video summarization on stored videos. |\n|Container | jps-gdino | Grounding DINO service that supports open vocabulary object detection for zero-shot object detection. |\n|Resources |Jetson Platform Services OSS Sources | Package that includes all third part OSS source code and licenses used across all Jetson Platform Services. |\n|Container |ialpha-ingress-arm64v8 | A reverse proxy that forwards incoming API requests to the appropriate microservice |\n|Container |its-monitoring | Used to monitor, persist, and visualize edge device status |\n|Container |jps-metric-exporter | Used to monitor system metrics and export to Promtheus for tracking |\n|Container |vst:x_aarch64 | Video Storage Toolkit microservice that enables discovery, storage and streaming of video sources | \n|Container |vst:x_aarch64 | NVStreamer container built for Jetson. Used to serve video files as RTSP streams. |\n|Container |vst:x_x86_64 | NVStreamer container built for x86. Can be used on x86 device to serve video files as RTSP streams. |\n|Container |emdx-analytics |Analytics service to create count analytics like line-crossing, Region of Interest (ROIs) and Field of View (FOV) |\n|Container |emdx-analytics-web-api | Provides APIs to interact with the Analytics service |\n|Container |sdr | Microservice to dynamically add & register streams to Deepstream, Analytic and Generative AI conatiners|\n|Container |sdr-reprovision-controller | Microservice to ensure SDR and VST stream lists are in sync|\n|Container |sdr-alertmanager-controller | A SDR sidecar container to process alerts sent by monitoring via Alertmanager|\n|Container |sdr-proxy-controller | An SDR sidecar container to convert request formatting to/from versions compatible with the main SDR container|\n\n\n## Developer Resources\n**Documentation** - [Jetson Platform Services](https://docs.nvidia.com/jetson/jps/moj-overview.html)\\\n**Documentation** - [Quick Start Guide](https://docs.nvidia.com/jetson/jps/setup/quick-start.html)\\\n**Blog** - [Bringing Generative AI to the Edge](https://developer.nvidia.com/blog/bringing-generative-ai-to-the-edge-with-nvidia-metropolis-microservices-for-jetson/) \\\n**Blog** - [Build Vision AI Applications with APIs](https://developer.nvidia.com/blog/how-to-build-vision-ai-applications-at-the-edge-with-nvidia-metropolis-microservices-and-apis/) \\\n**[Technical Whitepaper](https://resources.nvidia.com/en-us-metropolis-microservices-for-jetson/jetson-whitepaper) on Microservices for Jetson** \\\n**Webinar Part 1** - [Accelerate Edge AI Development With Metropolis APIs and Microservices on Jetson](https://info.nvidia.com/metropolis-on-jetson-webinar.html)\\\n**Webinar Part 2** - [How to Build With Metropolis Microservices for Jetson](https://info.nvidia.com/build-with-metropolis-microservices-for-jetson.html)\\\nLearn more about [Metropolis Microservices](https://developer.nvidia.com/metropolis-microservices)\n\n## License\nBy downloading or using the software and materials, you agree to the [License Agreement for Jetson Platform Services](https://docs.nvidia.com/jetson/jps/moj-license.html)","displayName",["D",1736980944878],"publisher","NVIDIA","latestVersion","collectionCounts","imageUrl","/api/image/nvidia/jps/resources/reference-workflow-and-resources","rawImageUrl","https://catalog.ngc.nvidia.com/_next/image?url=https%3A%2F%2Fassets.nvidiagrid.net%2Fngc%2Flogos%2FJetson.png&w=640&q=90","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_257":370,"_309":371,"_310":372,"_312":89},{"_257":367,"_309":368,"_310":369,"_312":89},{"_257":365,"_309":365,"_310":366,"_312":89},{"_257":362,"_309":363,"_310":364,"_312":89},{"_257":359,"_309":360,"_310":361,"_312":89},{"_257":357,"_309":357,"_310":358,"_312":89},{"_257":355,"_309":355,"_310":356,"_312":89},{"_257":352,"_309":353,"_310":354,"_312":89},{"_257":348,"_309":349,"_310":350,"_312":89},{"_257":346,"_309":346,"_310":347,"_312":89},{"_257":343,"_309":344,"_310":345,"_312":89},{"_257":340,"_309":341,"_310":342,"_312":89},{"_257":337,"_309":338,"_310":339,"_312":89},{"_257":334,"_309":335,"_310":336,"_312":89},{"_257":331,"_309":332,"_310":333,"_312":89},{"_257":329,"_309":329,"_310":330,"_312":89},{"_257":325,"_309":326,"_310":327,"_312":89},{"_257":322,"_309":322,"_310":323,"_312":89},{"_257":318,"_309":319,"_310":320,"_312":89},{"_257":314,"_309":315,"_310":316,"_312":89},{"_257":308,"_309":308,"_310":311,"_312":89},"VLM","value","filter",{"_313":89,"_309":308},"category","field","Vision 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We and our advertising partners will use this information to make our websites and the advertising displayed on it, more relevant to your interests.",5,[596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630],[469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485],{"_486":592,"_257":592,"_225":232,"_459":593},{"_486":587,"_257":587,"_225":232,"_459":588},{"_486":583,"_257":583,"_225":232,"_459":584},{"_486":578,"_257":578,"_225":232,"_459":579},{"_486":573,"_257":573,"_225":232,"_459":574},{"_486":561,"_257":561,"_225":232,"_459":562},{"_486":549,"_257":549,"_225":232,"_459":550},{"_486":544,"_257":544,"_225":232,"_459":545},{"_486":533,"_257":533,"_225":232,"_459":534},{"_486":528,"_257":528,"_225":232,"_459":529},{"_486":523,"_257":523,"_225":232,"_459":524},{"_486":518,"_257":518,"_225":232,"_459":519},{"_486":513,"_257":513,"_225":232,"_459":514},{"_486":508,"_257":508,"_225":232,"_459":509},{"_486":503,"_257":503,"_225":232,"_459":504},{"_486":496,"_257":496,"_225":232,"_459":497},{"_486":487,"_257":487,"_225":232,"_459":488},"hostName","amazon-adsystem.com",[489,490],{"_117":495,"_492":487,"_493":35,"_225":494},{"_117":491,"_492":487,"_493":35,"_225":494},"ad-privacy","host","isSession","This domain is owned by online retailer Amazon and is used as part of its affiliate marketing programme.","ad-id","doubleclick.net",[498,499],{"_117":502,"_492":496,"_493":35,"_225":501},{"_117":500,"_492":496,"_493":35,"_225":501},"IDE","This domain is owned by Doubleclick (Google). 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It typically acts as a third party host where website owners have placed one of its content sharing buttons in their pages, although its content and services can be embedded in other ways. Although such buttons add functionality to the website they are on, cookies are set regardless of whether or not the visitor has an active Linkedin profile, or agreed to their terms and conditions. For this reason it is classified as a primarily tracking/targeting domain.","twitter.com",[551,552,553,554],{"_117":560,"_492":549,"_493":35,"_225":556},{"_117":558,"_492":549,"_493":35,"_225":559},{"_117":557,"_492":549,"_493":35,"_225":556},{"_117":555,"_492":549,"_493":35,"_225":556},"personalization_id","This domain is owned by Twitter. The main business activity is: Social Networking Services. Where twitter acts as a third party host, it collects data through a range of plug-ins and integrations, that is primarily used for tracking and targeting.","guest_id_marketing","guest_id","Twitter does not currently provide information on the use of specific cookies.","guest_id_ads","youtube.com",[563,564,565,566],{"_117":572,"_492":561,"_493":35,"_225":570},{"_117":571,"_492":561,"_493":35,"_225":570},{"_117":569,"_492":561,"_493":35,"_225":570},{"_117":567,"_492":561,"_493":35,"_225":568},"VISITOR_INFO1_LIVE","This cookie is used as a unique identifier to track viewing of videos","__Secure-YNID","YouTube is a Google owned platform for hosting and sharing videos. 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It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier.","kndctr_F207D74D549850760A4C98C6_AdobeOrg_identity","_rdt_pn","www.nvidia.com","This cookie name is associated with www.mind.org.uk which is used for marketing purposes.","ai-podcast.nvidia.com","This cookie is used to identify the user's session on the website and is often associated with analytics or personalization.","_gcl_au","Used by Google AdSense for experimenting with advertisement efficiency across websites using their services","_mkto_trk","This cookie is associated with an email marketing service provided by Marketo. This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","_gat_gtag_UA_140825383_2","Google Analytics","_zitok","This cookie name is associated with ZoomInfo which is used to maintain a unique visitor identifier and store Personally Identifiable Information.","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","AMP_91bf70adfe","Supports Amplitude product analytics.","This cookie name is associated with StackAdapt Inc. which is used to support the effective management and optimization of digital advertising campaigns by handling information such as visitor actions on websites, visited pages, time spent, page load speed, and more.","build.nvidia.com","kndctr_F207D74D549850760A4C98C6_AdobeOrg_cluster","_cs_nnnnnnnnnnnnn","This is a session cookie. 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It is commonly used for analytics and personalization of content.","marketplace.nvidia.com","AMP_MKTG_92dea1e784","This cookie is typically associated with SnackTools, which is a suite of web applications for creating and sharing multimedia content. It is used to identify a user across sessions and track user activities.","forums.developer.nvidia.com","This cookie is typically associated with the use of Taptap Digital, a company specializing in digital advertising. It is used for tracking and ad personalization purposes.","_tt_enable_cookie","This cookie name is associated with TikTok which is used to collect data about behavior and purchases on the website and to measure the effect of advertising. It is also used to track website activity to help optimize advertising efforts.","AMCV_xxxxxAdobeOrg","This cookie is used to identify a unique visitor for tracking purposes by Adobe Experience Cloud.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.","ttcsid","This cookie name is associated with TikTok which is used to enable TikTok Ads session tracking by assigning a unique session ID to users who click on TikTok ads, allowing for the attribution of user behavior and conversions within the same session.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","AMP_MKTG_91bf70adfe","C0003","Personalization Cookies","These cookies collect data about how you have interacted with our website to help us improve your web experience, such as which pages you have visited. These cookies may store a unique ID so that our system will remember you when you return. They may be set by us or by third party providers whose services we have added to our pages. These cookies enable us to provide enhanced website functionality and personalization as well as make the marketing messages we send to you more relevant to your interests. If you do not allow these cookies, then some or all of these services may not function properly.",[718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738],[683,684,685,686,687],{"_486":578,"_257":578,"_225":232,"_459":709},{"_486":544,"_257":544,"_225":232,"_459":704},{"_486":697,"_257":697,"_225":232,"_459":698},{"_486":693,"_257":693,"_225":232,"_459":694},{"_486":688,"_257":688,"_225":232,"_459":689},"nvcrm.my.site.com",[690],{"_117":691,"_492":688,"_493":35,"_225":692},"BrowserId","If you know anything about this cookie and its uses that are not specific to a particular site please add your contributions.","nvidia.partners",[695],{"_117":696,"_492":693,"_493":35,"_225":527},"edge","github.com",[699,700],{"_117":703,"_492":697,"_493":35,"_225":702},{"_117":701,"_492":697,"_493":35,"_225":702},"logged_in","This domain is owned by Github. 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The data is aggregated and analyzed; therefore, it remains anonymous upon use.\n","nvHeadless","This cookie is likely used to track if a user is using the site in a 'headless' non-GUI mode, which could be for accessibility reasons or for automated processes.","_biz_nA","C0002","Performance Cookies","These cookies are used to provide quantitative measures of our website visitors, such as the number of times you visit, time on page, your mouse movements, scrolling, clicks and keystroke activity on the websites; other browsing, search, or product research behavior; and what brought you to our site. These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website 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	Files	Compressed Size
2.0.1Selected	6	46.33 MB	January 15, 2025 UTC
2.0.0	6	46.33 MB	December 20, 2024 UTC
1.1.0	8	33.98 MB	June 13, 2024 UTC