python3 run_nsight_streamer.py -v /home/user/reports ngfx

","code-1ufofd","

python run_nsight_streamer.py -v d:\\reports ngfx

","code--7y1fd0","

docker run -it --rm -p 8080:8080 -p 3478:3478 --gpus all --runtime nvidia -v /host_path/reports:/container_path/reports nvcr.io/nvidia/devtools/nsight-streamer-ngfx:2026.1.0

","code--kgh3g9","

docker run -it --rm -p 8080:8080 -p 3478:3478 --gpus all --runtime nvidia \\\n  -e NVIDIA_DRIVER_CAPABILITIES=all \\\n  -v /host_path/reports:/container_path/reports \\\n  nvcr.io/nvidia/devtools/nsight-streamer-ngfx:2026.1.0

","code-v32y5d","

    helm install --wait --set tool=ngfx \\\n      --set volumes[0].name=reports-volume \\\n      --set volumes[0].persistentVolumeClaim.claimName=your-reports-pvc \\\n      --set volumeMounts[0].name=reports-volume \\\n      --set volumeMounts[0].mountPath=/mnt/host/volumes/reports \\\n      nsight-streamer https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz

","code-va8bwi","

    # values.yaml\n    tool: ngfx\n    volumes:\n      - name: reports-volume\n        persistentVolumeClaim:\n          claimName: your-reports-pvc\n    volumeMounts:\n      - name: reports-volume\n        mountPath: /mnt/host/volumes/reports

","code-un4djv","

    helm install --wait -f values.yaml nsight-streamer \\\n        https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz

","code-onlktu","

    helm install --wait -f values.yaml nsight-streamer \\\n        https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz --namespace example-ns

","code-nq2nvx","

    helm install --wait --generate-name -f values.yaml \\\n        https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz

","code--l4u1m2","

kubectl port-forward service/nsight-streamer-service 30080:30080 30478:30478

","code-c35bqi","

kubectl logs job/nsight-streamer-print-connection-info

","code--6e2hna","

http://<node-ip>:<node-port>

","code--3bd776","run_nsight_streamer.py","code-161","-v","code-qa4kvu","--volume","code--ltj71x","docker run","code--5m5003","/host_path/reports","code--7cncqm","/container_path/reports","code-plww2","--set","code--slfr0f","ClusterIP","code-lgjf93","service.type=ClusterIP","code-u4jxki","http://localhost:30080","code-jn2car","NodePort","code-uf55sd","service.type=NodePort","code--5tps7w","service.nodeHttpPort","code--o9xgja","chrome://flags/#unsafely-treat-insecure-origin-as-secure","code--vkhs2p","Connection failed","code-nz8zbj","about:config","code-ejrkky","media.peerconnection.ice.loopback","code-1axlo","File","code-1aloe","Exit","nvidia/devtools/nsight-streamer-ngfx","nvidia/devtools/containers/nsight-streamer-ngfx","nsight-streamer-ngfx","A self-hosted NVIDIA Nsight Tools GUI (for Nsight Graphics) running in a Docker container allows for remote access via a web browser.","# Nsight Streamer for Nsight Graphics\n\nA self-hosted NVIDIA Nsight Tools GUI, running within a Docker container, enables remote access through a web browser. This configuration is highly beneficial for analyzing data on remote servers or clusters.\n\nCurrently, NVIDIA Nsight Systems, NVIDIA Nsight Compute, NVIDIA Nsight Graphics, and NVIDIA Nsight Deep Learning Designer are supported for running inside a container.\n\n\n## Benefits\n\n- **Handling Large Data**: The reports generated by NVIDIA Nsight Graphics on servers/clusters can be extremely large, making it impractical to transfer them to a local machine. By hosting the GUI on the remote server, you can analyze the data in place without the need for excessive data transfers.\n\n- **Enhanced Performance**: Remote servers or clusters often have significantly more computational power and memory compared to local machines. Analyzing the reports directly on the remote server leverages these resources, ensuring faster and more efficient data processing and analysis.\n\n- **Security Compliance**: Many organizations have strict security protocols that prevent copying sensitive data from servers or clusters to local environments. This self-hosted solution ensures that the data remains within the secure confines of the server while still providing the necessary tools for thorough analysis.\n\n## Warning\n\nNsight Streamer for Nsight Graphics supports remote profiling, so it is essential to ensure that the server is secure and that the necessary security measures are in place to prevent unauthorized access to your data.\n\n## Getting Started\n\n### Prerequisites\n\n#### Docker\n\n- [Docker](https://docs.docker.com/get-docker/) installed on the host machine.\n- NVIDIA drivers installed on the host machine. See the [NVIDIA GPU Driver Installation Guide](https://docs.nvidia.com/datacenter/tesla/driver-installation-guide/) for more information.\n- [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) installed on the host machine.\n\n#### Kubernetes\n\n- A [Kubernetes cluster](https://kubernetes.io/docs/setup/).\n- [Helm](https://helm.sh/docs/intro/install/) installed on the administator machine.\n- Have NVIDIA GPU Operator installed on the Kubernetes cluster. See the [NVIDIA GPU Operator Installation Guide](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/getting-started.html#operator-install-guide) for more information.\n\n#### (Optional) NVIDIA GPU with AV1 encoding support\n\n- NVIDIA GPU with AV1 encoding support (Ada Lovelace architecture or newer GPUs). For a complete list of supported GPUs, see the [NVIDIA Video Encode and Decode GPU Support Matrix](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new)\n\n\n\n### Run the container using a Python script\n\nThe Nsight Streamer can be started using the `run_nsight_streamer.py` script provided by [Nsight Streamer Resources](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/devtools/resources/nsight-streamer-resources).\n\n#### Linux/Mac\n\n```\npython3 run_nsight_streamer.py -v /home/user/reports ngfx\n```\n\n#### Windows\n\n```\npython run_nsight_streamer.py -v d:\\reports ngfx\n```\n\n#### Benefits\n\n- **Fetching the Latest Image**: The script fetches the latest image of the specified Docker container from the NGC repository. This ensures you are always running the most up-to-date version of the container.\n- **Port Availability**: The script checks if HTTP and TURN ports (8080 and 3478 by default) are available on the host machine. If they are not available, it finds an available port and uses that for the container.\n- **Stopping Existing Containers**: Before starting a new container, the script can stop existing Nsight Streamer containers which are using the specified HTTP and TURN ports.\n- **Running the Container**: The script constructs and runs the Docker command with the specified parameters, including volumes and additional Docker arguments.\n- **Configuration Preserve**: The script automatically preserves Nsight Tool configuration across multiple container launches on one machine.\n- **Hardware Acceleration**: The script automatically detects the availability of a NVIDIA GPU with AV1 encoding support and NVIDIA Container Toolkit and enables hardware acceleration if both are present. NVIDIA GPU with AV1 encoding support is required for hardware acceleration. See the [NVIDIA Video Encode and Decode GPU Support Matrix](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new) for a list of supported GPUs. Additionaly, NVIDIA drivers are required for hardware acceleration. See the [NVIDIA GPU Driver Installation Guide](https://docs.nvidia.com/datacenter/tesla/driver-installation-guide/) for more information.\n\n#### Script arguments\n\nNone of the arguments are required, but it is highly recommended to include at least one `-v`/`--volume` argument to mount a volume with profiling reports inside the container.\n\n| Parameter | Description | Default Value |\n| :------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------ |\n| tool | The Nsight Tool tool to run inside the container. | |\n| --http-port | Set the HTTP port. Set to 'dynamic' to find the first available port. | 8080 |\n| --turn-port | Set the TURN port. Set to 'dynamic' to find the first available port. | 3478 |\n| --host-ip | The host IP address to bind the server to. | 0.0.0.0 |\n| --enable-resize | Should resizing be enabled to fit the remote resolution to the client window? | true |\n| --max-resolution | Maximum resolution of the remote screen used for streaming Nsight Tool. | 1920x1080 |\n| -v, --volume | Mount a volume from the host to the container. This option can be repeated multiple times. The volume will be mount to /mnt/host/volumes/[volume] inside the container | |\n| --no-preserve-config | Do not preserve a Nsight Tool configuration file in the container between runs. | |\n| -y, --yes | Automatically answer 'yes' to prompts. Use with caution. | |\n| --web-username | The username for accessing the NVIDIA Nsight Streamer from a browser. If set to an empty string, no authentication is required. | |\n| --web-password | The password for accessing the NVIDIA Nsight Streamer from a browser. | |\n| --encoder | Manually specify the encoder to use (nvav1enc, vp9). If not specified, the container will auto-detect the best available encoder. | |\n| -- | Additional docker run arguments that will be passed directly to the docker run command. | |\n| -h, --help | Display this help and exit. | |\n\n### Run the container using `docker run`\n\n1. From the top-right corner of this page, select the pull-down Get Container and copy the URL to the default container. Alternatively, click on View all tags to select a different container.\n2. Open a command prompt on your Linux compatible system and run the following command. Ensure the pull completes successfully before proceeding to the next step.\n3. Run the docker container (use the desired container tag in the command line below):\n\n```bash\ndocker run -it --rm -p 8080:8080 -p 3478:3478 --gpus all --runtime nvidia -v /host_path/reports:/container_path/reports nvcr.io/nvidia/devtools/nsight-streamer-ngfx:2026.1.0\n```\n\nThis example sets the HTTP port for publishing on the host to 8080, the TURN port for publishing on the host to 3478, and mounts `/host_path/reports` to `/container_path/reports` inside the container.\n\n#### Enabling Hardware Acceleration\n\nTo enable GPU hardware acceleration with Docker which improves the performance of the Nsight Streamer, you need to:\n\n1. Have an NVIDIA GPU with AV1 encoding support on the node where the Nsight Streamer is deployed (Ada Lovelace architecture or newer GPUs). For a complete list of supported GPUs, see the [NVIDIA Video Encode and Decode GPU Support Matrix](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new)\n2. Have NVIDIA drivers installed on the host. See the [NVIDIA GPU Driver Installation Guide](https://docs.nvidia.com/datacenter/tesla/driver-installation-guide/) for more information.\n3. Have NVIDIA Container Toolkit installed. See the [NVIDIA Container Toolkit Installation Guide](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) for more information.\n4. Pass the appropriate flags to Docker:\n\n```bash\ndocker run -it --rm -p 8080:8080 -p 3478:3478 --gpus all --runtime nvidia \\\n -e NVIDIA_DRIVER_CAPABILITIES=all \\\n -v /host_path/reports:/container_path/reports \\\n nvcr.io/nvidia/devtools/nsight-streamer-ngfx:2026.1.0\n```\n\n\n### Runtime environment variables\n\nCan be used to configure runtime parameters.\n\n| Variable | Description | Default value |\n| :------------- | :-------------------------------------------------------------------------------------------------------------------------------- | :------------ |\n| TURN_PORT | TCP port that will be used for WebRTC data transmission. The port should match the port published from the container on the host. | 3478 |\n| ENABLE_RESIZE | Should resizing be enabled to fit the remote resolution to the client window? | true |\n| MAX_RESOLUTION | Maximum resolution of the remote screen used for streaming the Nsight Tool. | 1920x1080 |\n| WEB_USERNAME | The username for accessing the NVIDIA Nsight Streamer from a browser. If set to an empty string, no authentication is required. | nvidia |\n| WEB_PASSWORD | The password for accessing the NVIDIA Nsight Streamer from a browser. | nvidia |\n| ENCODER | The video encoder to use (nvav1enc for NVIDIA GPU with AV1 support, vp9 for software encoding). | Auto-detected |\n\n\n### Run in a Kubernetes cluster using a Helm Chart\n\n- Install the Nsight Streamer with volumes for your profiling reports:\n\n ```bash\n helm install --wait --set tool=ngfx \\\n --set volumes[0].name=reports-volume \\\n --set volumes[0].persistentVolumeClaim.claimName=your-reports-pvc \\\n --set volumeMounts[0].name=reports-volume \\\n --set volumeMounts[0].mountPath=/mnt/host/volumes/reports \\\n nsight-streamer https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz\n ```\n\n- Using a values file for more complex configurations:\n\n ```yaml\n # values.yaml\n tool: ngfx\n volumes:\n - name: reports-volume\n persistentVolumeClaim:\n claimName: your-reports-pvc\n volumeMounts:\n - name: reports-volume\n mountPath: /mnt/host/volumes/reports\n ```\n\n ```bash\n helm install --wait -f values.yaml nsight-streamer \\\n https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz\n ```\n\n- Install in a non-default namespace:\n\n ```bash\n helm install --wait -f values.yaml nsight-streamer \\\n https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz --namespace example-ns\n ```\n\n- Install multiple copies of the Nsight Streamer:\n\n ```bash\n helm install --wait --generate-name -f values.yaml \\\n https://helm.ngc.nvidia.com/nvidia/devtools/charts/nsight-streamer-2026.2.2.tgz\n ```\n\n### Enabling Hardware Acceleration in Kubernetes\n\nTo enable GPU hardware acceleration for video encoding in Kubernetes, which significantly improves the performance and responsiveness of the Nsight Streamer, you need to:\n\n1. Have an NVIDIA GPU with AV1 encoding support on the node where the Nsight Streamer is deployed (Ada Lovelace architecture or newer GPUs). For a complete list of supported GPUs, see the [NVIDIA Video Encode and Decode GPU Support Matrix](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new)\n\n\n\n\n#### Helm installation configuration values\n\nThe Nsight Streamer can be customized to suit particular needs. [A values file](https://helm.sh/docs/chart_template_guide/values_files/) or the `--set` argument can be used for setting these values.\n\n| Parameter | Description | Default Value |\n| -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------- |\n| tool | The Nsight tool to run in the container. Valid values: nsys (Nsight Systems), ncu (Nsight Compute), ngfx (Nsight Graphics), ndld (Nsight Deep Learning Designer). | Required |\n| service.type | The type of Kubernetes service to create (ClusterIP, NodePort). | NodePort |\n| service.httpPort | The port on which the HTTP service will be exposed within the cluster. | 30080 |\n| service.turnPort | The port on which the TURN service will be exposed within the cluster. | 30478 |\n| service.nodeHttpPort | The NodePort value for exposing HTTP traffic outside the cluster. Applicable when service.type is NodePort. | 30080 |\n| service.nodeTurnPort | The NodePort value for exposing TURN traffic outside the cluster. Applicable when service.type is NodePort. Should be equal to service.turnPort. | 30478 |\n| nodeSelector | Node selector for Nsight Streamer pod scheduling. | {} |\n| tolerations | Tolerations for Nsight Streamer pod scheduling. | [] |\n| affinity | Affinity rules for Nsight Streamer pod scheduling. | {} |\n| volumeMounts | List of volumes to mount into the container. | [] |\n| volumes | List of volumes to be used by the container. | [] |\n| env | List of environment variables to be injected into the Docker container. | [] |\n| enableResize | Should resizing be enabled to fit the remote resolution to the client window? | true |\n| maxResolution | Maximum resolution of the remote screen used for streaming the Nsight Tool. | 1920x1080 |\n| preserveConfig | Preserve the Nsight Tool configuration file in the container between runs. | true |\n| webUsername | The username for accessing the NVIDIA Nsight Streamer from a browser. Can be provided as a direct string value or as a secret reference. If using a secret, set webUsername as a map with secretName and secretKey. If set to an empty string, no authentication is required. | nvidia |\n| webPassword | The password for accessing the NVIDIA Nsight Streamer from a browser. Can be provided as a direct string value or as a secret reference. If using a secret, set webPassword as a map with secretName and secretKey. | nvidia |\n\n\n#### Accessing the Service After Installation\n\nAfter installing the Nsight Streamer using Helm, you can access it in different ways depending on the service type configuration:\n\n##### ClusterIP Service Type\n\nWhen using `ClusterIP` (set via `service.type=ClusterIP`), the service is only accessible from within the cluster. You can access it using port forwarding to your local machine:\n\n```bash\nkubectl port-forward service/nsight-streamer-service 30080:30080 30478:30478\n```\n\nThen access the service at `http://localhost:30080`\n\nMake sure that the target turn port forwarded is the same as the service.turnPort (default is 30478).\n\n##### NodePort Service Type\n\nWhen using `NodePort` (default, or set via `service.type=NodePort`), the service is exposed on each node's IP at a static port. The default port is 30080, but this can be configured during installation using the `service.nodeHttpPort` parameter.\n\nAfter installation, the connection information will be automatically displayed by the print-connection-info job. You can retrieve this information by checking the job logs:\n```bash\nkubectl logs job/nsight-streamer-print-connection-info\n```\n\nAccess the service by opening your web browser and navigating to:\n```\nhttp://:\n```\n\nNote: Ensure your network security settings allow access to the configured NodePort.\n\n\n\n### Automatic Report File Detection\n\nThe Nsight Streamer scans all mounted volumes at startup and selects the first one containing supported report files (ngfx-cppcap, nsight-gfxcppcap). The \"Open...\" dialog will be opened with the detected directory.\n\n\n## Troubleshooting\n\n### Clipboard is not working in Chrome\n\nEnable `chrome://flags/#unsafely-treat-insecure-origin-as-secure` and add the Nsight Streamer URL to the list.\n\n### `Connection failed` on Firefox\n\nIf you encounter a \"Connection failed.\" error on Firefox, you can resolve it by changing a configuration setting:\n\n- Open Firefox and navigate to `about:config`.\n- Search for `media.peerconnection.ice.loopback`.\n- Set the value to true.\n\n### `Connection failed` on Safari\n\nIf you are experiencing connection issues in Safari when using AV1 codec:\n\n- Open Safari and go to Safari menu > Settings > Advanced.\n- Check the box next to \"Show features for web developers\".\n- Go to \"Feature Flags\" and search for \"WebRTC AV1 codec\".\n- Enable the \"WebRTC AV1 codec\" option.\n- Restart Safari and try connecting again.\n\n### The GUI is too small on an HDPI screen\n\nRestart the remote Nsight Tool:\n\n- Go to `File` in the menu bar of Nsight Tool.\n- Select `Exit`.\n- Nsight Tool will be opened with the scaled GUI.\n\n## License Agreements\n\nBy pulling and using the container, you accept the terms and conditions of this [End User License Agreement](https://docs.nvidia.com/nsight-graphics/CopyrightAndLicenses/index.html).\n\n## Suggested Reading\n\n[Getting Started with Nsight Graphics](https://developer.nvidia.com/nsight-graphics/get-started)","NVIDIA Nsight Streamer for Nsight Graphics",["D",1776141774648],[214,251,249,247,244],"/api/image/nvidia/devtools/containers/nsight-streamer-ngfx",4221869862,"hasSignedTag",[],[337],[],[333],[],{"_93":334,"_126":334,"_127":335,"_129":336},"signed images",{"_131":336,"_126":334},"system",{"_93":125,"_126":125,"_127":338,"_129":130},{"_131":130,"_126":125},{"_159":1518,"_161":1519},"ngcApps",[1471],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1453":1454,"_1455":1456,"_1457":1458,"_1459":1460,"_1461":350,"_187":374,"_1462":1463,"_1451":51,"_1464":139,"_1465":139,"_1466":1467,"_1468":139,"_1469":1470},"amplitude",{"_1449":1450,"_1451":51,"_1045":-7,"_1452":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmNoaW5hTmltRGlzdHJpYnV0b3JzUmVkZXNpZ24lMjIlM0F0cnVlJTJDJTIyZW5hYmxlQ3NhV2lkZ2V0JTIyJTNBZmFsc2UlMkMlMjJlbmFibGVQcm9kdWN0R3JvdXBpbmdCeVN1YnNjcmlwdGlvbiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1443":1444,"_1445":1446,"_1447":1448},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.2.3","defaultSearchSuggestions",{"_1320":453,"_1321":1322,"_1323":1324,"_1325":1326},"announcements",[],"consentState",{"_411":1310,"_1311":139,"_1312":26,"_1313":26,"_1314":1315},"consentConfig",{"_393":394,"_395":396,"_397":398,"_399":400,"_401":402,"_403":404,"_405":406,"_407":408,"_409":410,"_411":412},"showContactAdmin",1782192733497,[],[],[388,389,390,391,392],{"_40":62,"_42":67,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":62,"_42":65,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":45,"_46":47,"_48":54,"_50":51},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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They are capable of tracking your browser across other sites and building up a profile of your interests. This may impact the content and messages you see on other websites you visit. If you do not allow these cookies you may not be able to use or see these sharing tools.","alwaysActive","order",11,"cookies",[],"hosts",[],"C0004","Advertising Cookies","These cookies record your visit to our websites, the pages you have visited and the links you have followed to influence the advertisements that you see on other websites. These cookies and the information they collect may be managed by other companies, including our advertising partners, and may be used to build a profile of your interests and show you relevant advertising on other sites. We and our advertising partners will use this information to make our websites and the advertising displayed on it, more relevant to your interests.",[562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596],[434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450],{"_451":558,"_93":558,"_92":453,"_425":559},{"_451":553,"_93":553,"_92":453,"_425":554},{"_451":549,"_93":549,"_92":453,"_425":550},{"_451":544,"_93":544,"_92":453,"_425":545},{"_451":539,"_93":539,"_92":453,"_425":540},{"_451":527,"_93":527,"_92":453,"_425":528},{"_451":515,"_93":515,"_92":453,"_425":516},{"_451":510,"_93":510,"_92":453,"_425":511},{"_451":499,"_93":499,"_92":453,"_425":500},{"_451":494,"_93":494,"_92":453,"_425":495},{"_451":489,"_93":489,"_92":453,"_425":490},{"_451":484,"_93":484,"_92":453,"_425":485},{"_451":479,"_93":479,"_92":453,"_425":480},{"_451":474,"_93":474,"_92":453,"_425":475},{"_451":469,"_93":469,"_92":453,"_425":470},{"_451":462,"_93":462,"_92":453,"_425":463},{"_451":452,"_93":452,"_92":453,"_425":454},"hostName","amazon-adsystem.com","",[455,456],{"_245":461,"_458":452,"_459":26,"_92":460},{"_245":457,"_458":452,"_459":26,"_92":460},"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",[464,465],{"_245":468,"_458":462,"_459":26,"_92":467},{"_245":466,"_458":462,"_459":26,"_92":467},"IDE","This domain is owned by Doubleclick (Google). 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It is used as a URL shortening service, which allows Twitter to collect data on how links are shared.","snowplow.com",[491],{"_245":492,"_458":489,"_459":26,"_92":493},"sp","Testing","google.com",[496],{"_245":497,"_458":494,"_459":26,"_92":498},"NID","This domain is owned by Google Inc. Although Google is primarily known as a search engine, the company provides a diverse range of products and services. Its main source of revenue however is advertising. Google tracks users extensively both through its own products and sites, and the numerous technologies embedded into many millions of websites around the world. It uses the data gathered from most of these services to profile the interests of web users and sell advertising space to organisations based on such interest profiles as well as aligning adverts to the content on the pages where its customer's adverts appear.","tags.srv.stackadapt.com",[501,502,503,504],{"_245":509,"_458":499,"_459":26,"_92":506},{"_245":508,"_458":499,"_459":26,"_92":506},{"_245":507,"_458":499,"_459":26,"_92":506},{"_245":505,"_458":499,"_459":26,"_92":506},"sa-user-id-v3","This domain is associated with StackAdapt, a platform for programmatic advertising, which suggests that it is used for targeting and advertising purposes.","sa-user-id","sa-user-id-v2","sa-user-id-v4","linkedin.com",[512],{"_245":513,"_458":510,"_459":26,"_92":514},"bcookie","This domain is owned by LinkedIn, the business networking platform. 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",[517,518,519,520],{"_245":526,"_458":515,"_459":26,"_92":522},{"_245":524,"_458":515,"_459":26,"_92":525},{"_245":523,"_458":515,"_459":26,"_92":522},{"_245":521,"_458":515,"_459":26,"_92":522},"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",[529,530,531,532],{"_245":538,"_458":527,"_459":26,"_92":536},{"_245":537,"_458":527,"_459":26,"_92":536},{"_245":535,"_458":527,"_459":26,"_92":536},{"_245":533,"_458":527,"_459":26,"_92":534},"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.",[684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,703,704],[649,650,651,652,653],{"_451":544,"_93":544,"_92":453,"_425":675},{"_451":510,"_93":510,"_92":453,"_425":670},{"_451":663,"_93":663,"_92":453,"_425":664},{"_451":659,"_93":659,"_92":453,"_425":660},{"_451":654,"_93":654,"_92":453,"_425":655},"nvcrm.my.site.com",[656],{"_245":657,"_458":654,"_459":26,"_92":658},"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",[661],{"_245":662,"_458":659,"_459":26,"_92":493},"edge","github.com",[665,666],{"_245":669,"_458":663,"_459":26,"_92":668},{"_245":667,"_458":663,"_459":26,"_92":668},"logged_in","This domain is owned by Github. 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We have categorized it under Functionality because it is necessary for the operation of our affiliate program.","nv.modal.cuda","This cookie name suggests it is related to a modal popup functionality on NVIDIA's website, possibly to remember user preferences or interactions with the modal.","readme_library","docs.api.nvidia.com","_im_ses.1006927","geo_locator","nv.modal.deepstream","openedx-language-preference","learn.nvidia.com","doxygen_width","raytracing-docs.nvidia.com","This cookie is likely used to remember the width preferences of a sidebar or interface element within a documentation platform like Doxygen.","_sfid_eb78","This cookie is categorized as Functionality Cookie.","_im_id.1006927","_hjUserAttributesHash","docs.nvidia.com","This cookie name is associated with Hotjar which is used to know when any user attribute has changed and needs to be updated.","mbox","Cookie set by Adobe SiteCatalyst analytics software - used for measuring the performance of page content using A/B split testing","nv.modal.cudnn","This cookie name suggests it is related to modal popup handling or user interface preferences on NVIDIA's website, specifically for the cuDNN library section.","readme_language","nv.modal.hpc","This cookie name suggests it is related to a modal pop-up on a website, possibly to control the display of a high-priority cookie notice or other important information to the user.","at_check","Used by Adobe Target to check if cookies are enabled/supported on the browser","_biz_uid","This cookie is used to record website and server performance with each visit to the site. 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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