Parabricks_umi_fgbio

The Parabricks umi_fgbio Container houses accelerated fgbio toolkit which utilizes molecular tagging (UMIs) to distinguish actual biological variants from machine sequencing errors, ensuring high-fidelity genomic data analysis

Description

This UMI pipeline is based on Fulcrum Genomics toolkit, processes sequencing reads with\nmolecular barcodes (also known as Unique Molecular Indices, UMIs), which provide\nimpressive error correction and increased accuracy using a sequencing consensus read level.

UMI data can be processed using the workflow based on fgbio methods. The tools can be run\nin a standalone fashion or the whole set of tools can be run using one command.

The container components are ready for commercial/non-commercial use.

License/Terms of Use:

Use of this software is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for NVIDIA AI Products.

Deployment Geography:

Global

Release Date:

NGC - 01/13/2026

Program Classes

A GPU-accelerated software for processing UMI-tagged DNA sequencing reads to produce error-corrected consensus reads for downstream genomic analysis.

Deployment Details:

Our accelerated fgbio tool is designed and optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware parallelism and optimized software frameworks, the toolkit achieves significantly faster genomic data processing and consensus calling times compared to standard CPU-based Java implementations

Reference(s):

Fennell, T., Homer, N., & Fulcrum Genomics. (n.d.). fgbio: Tools for working with genomic and high throughput sequencing data, GitHub. https://github.com/fulcrumgenomics/fgbio

Container Version(s):

v1.4.0

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure this container meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

Get Help

Enterprise Support

Get access to knowledge base articles and support cases or submit a ticket.

Quick Start Run Commands

Dual Header

pbrun umi_fgbio --in-fq firstInput.fastq.gz secondInput.fastq.gz \\\n    --ref theReferenceFile.fasta \\\n    --out-dir directoryWithOutput \\\n    --umi-in-header \\\n    --strategy paired\n

Dual Read

pbrun umi_fgbio --in-fq firstInput.fastq.gz secondInput.fastq.gz \\\n    --ref theReferenceFile.fasta \\\n    --out-dir directoryWithOutput \\\n    --strategy paired \\\n    --read-structures 7M1B+T 7M1B+T\n

Dual Separate

pbrun umi_fgbio --in-fq secondInput.fastq.gz fourthInput.fastq.gz firstInput.fastq.gz thirdInput.fastq.gz \\\n    --ref theReferenceFile.fasta \\\n    --out-dir directoryWithOutput \\\n    --strategy paired \\\n    --read-structures 1B+T +T 7M 7M\n

Single Header

pbrun umi_fgbio --in-fq firstInput.fastq.gz secondInput.fastq.gz \\\n    --ref theReferenceFile.fasta \\\n    --out-dir directoryWithOutput \\\n    --umi-in-header \\\n    --strategy adjacency\n

Single Separate

pbrun umi_fgbio --in-fq secondInput.fastq.gz fourthInput.fastq.gz firstInput.fastq.gz \\\n    --ref theReferenceFile.fasta \\\n    --out-dir directoryWithOutput \\\n    --strategy adjacency \\\n    --read-structures 1B+T +T 7M\n

Input/Output file options

--in-fq [IN_FQ [IN_FQ ...]]\n    Path to one or more fastq files, each corresponding to\n    a sub-read. Files can be in fastq or fastq.gz format.\n    (default: None)\n\n    **Option is required.**\n\n\n--ref REF\n    Path to the reference file (default: None)\n\n    **Option is required.**\n\n\n--metadata METADATA\n    Path to a file containing the metadata about the\n    samples. If no file is provided, output reads will be\n    put into unmatched files only. (default: None)\n\n\n--out-dir OUT_DIR\n    Path to the directory that will contain all of the\n    generated files.\n    (default: None)\n\n    **Option is required.**\n

Pipeline Options

--umi-in-header\n    Specifies that UMIs are in the read header. (default:\n    False)\n\n\n-L INTERVAL, --interval INTERVAL\n    Interval within which to call bqsr from the input\n    reads. All intervals will have a padding of 100 to get\n    read records, and overlapping intervals will be\n    combined. Interval files should be passed using the\n    --interval-file option. This option can be used\n    multiple times (e.g. \"-L chr1 -L chr2:10000 -L\n    chr3:20000+ -L chr4:10000-20000\") (default: None)\n\n\n--bwa-options BWA_OPTIONS\n    Pass supported bwa mem options as one string. The\n    current original bwa mem supported options are -M, -Y,\n    -T (e.g. --bwa-options=\"-M -Y\") (default: None)\n\n\n--no-warnings\n    Suppress warning messages about system thread and\n    memory usage. (default: None)\n\n\n--read-group-sm READ_GROUP_SM\n    SM tag for read groups in this run. (default: None)\n\n\n--read-group-lb READ_GROUP_LB\n    LB tag for read groups in this run. (default: None)\n\n\n--read-group-pl READ_GROUP_PL\n    PL tag for read groups in this run. (default: None)\n\n\n--read-group-id-prefix READ_GROUP_ID_PREFIX\n    Prefix for the ID and PU tags for read groups in this\n    run. This prefix will be used for all pairs of fastq\n    files in this run. The ID and PU tags will consist of\n    this prefix, and an identifier that will be unique for\n    a pair of fastq files. (default: None)\n\n\n-ip INTERVAL_PADDING, --interval-padding INTERVAL_PADDING\n    Amount of padding (in base pairs) to add to each\n    interval you are including. (default: None)\n\n\n--read-structures [READ_STRUCTURES [READ_STRUCTURES ...]]\n    The read structure for each of the FASTQs. There must\n    be one read structure per input fastq file. (default:\n    None)\n\n\n--no-barcode\n    Remove the requirement that input read structures must\n    contain sample barcodes. (default: None)\n\n\n--out-metrics OUT_METRICS\n    The file to which per-barcode metrics are written in\n    the output directory. If none given, a file named\n    demux_barcode_metrics.txt will be written to the\n    output directory. If UMIs are in read header, no\n    metrics file will be generated. (default: None)\n\n\n--num-zip-threads NUM_ZIP_THREADS\n    Number of CPUs to use for zipping BAM files in a run\n    (default 16 for coordinate sorts and 10 otherwise).\n    (default: None)\n\n\n--num-sort-threads NUM_SORT_THREADS\n    Number of CPUs to use for sorting in a run (default 10\n    for coordinate sorts and 16 otherwise). (default:\n    None)\n\n\n--max-records-in-ram MAX_RECORDS_IN_RAM\n    Maximum number of records in RAM when using a\n    queryname or template coordinate sort mode; lowering\n    this number will decrease maximum memory usage.\n    (default: 65000000)\n\n\n--mem-limit MEM_LIMIT\n    Memory limit in GBs during sorting and postsorting. By\n    default, the limit is half of the total system memory. \n    (default: 1007)\n\n\n--gpuwrite\n    Use one GPU to accelerate writing final BAM/CRAM.\n    (default: None)\n\n\n--gpuwrite-deflate-algo GPUWRITE_DEFLATE_ALGO\n    Choose the nvCOMP DEFLATE algorithm to use with\n    --gpuwrite. Note these options do not correspond to CPU\n    DEFLATE options. Valid options are 1, 2, and 4. Option\n    1 is fastest, while options 2 and 4 have progressively\n    lower throughput but higher compression ratios. The\n    default value is 1 when the user does not provide an\n    input (i.e., None) (default: None)\n\n\n--gpusort\n    Use GPUs to accelerate sorting and marking.\n    (default: None)\n\n\n--strategy STRATEGY\n    The UMI assignment strategy, which can be adjacency or\n    paired. (default: )\n\n    **Option is required.**\n\n\n--min-map-q MIN_MAP_Q\n    Minimum mapping quality. (default: 30)\n\n\n--num-worker-threads NUM_WORKER_THREADS\n    Number of threads for worker. (default: 14)\n\n\n--error-rate-pre-umi ERROR_RATE_PRE_UMI\n    The Phred-scaled error rate for an error prior to the\n    UMIs being integrated. (default: 45)\n\n\n--error-rate-post-umi ERROR_RATE_POST_UMI\n    The Phred-scaled error rate for an error post the UMIs\n    have been integrated. (default: 40)\n\n\n--min-input-base-quality MIN_INPUT_BASE_QUALITY\n    Ignore bases in raw reads that have Q below this\n    value. (default: 10)\n\n\n--min-consensus-base-quality MIN_CONSENSUS_BASE_QUALITY\n    Mask (make ‘N’) consensus bases with quality less than\n    this threshold. (default: 2)\n\n\n--min-reads MIN_READS\n    The minimum number of reads to produce a consensus\n    base. (default: 1)\n\n\n--out-suffixF OUT_SUFFIXF\n    Output suffix used for paired reads that are first in\n    pair. The suffix must end with \".gz\" (default:\n    _1.fastq.gz)\n\n\n--out-suffixF2 OUT_SUFFIXF2\n    Output suffix used for paired reads that are second in\n    pair. The suffix must end with \".gz\" (default:\n    _2.fastq.gz)\n\n\n--out-suffixO OUT_SUFFIXO\n    Output suffix used for orphan/unmatched reads that are\n    first in pair. The suffix must end with \".gz\". If no\n    suffix is provided, these reads will be ignored\n    (default: None)\n\n\n--out-suffixO2 OUT_SUFFIXO2\n    Output suffix used for orphan/unmatched reads that are\n    second in pair. The suffix must end with \".gz\". If no\n    suffix is provided, these reads will be ignored\n    (default: None)\n\n\n--out-suffixS OUT_SUFFIXS\n    Output suffix used for single-end/unpaired reads. The\n    suffix must end with \".gz\". If no suffix is provided,\n    these reads will be ignored (default: None)\n\n\n--rg-tag RG_TAG\n    Split reads into different fastq files based on the\n    read group tag. Must be either PU or ID (default:\n    None)\n\n\n--remove-qc-failure\n    Remove reads from the output that have abstract QC\n    failure. (default: None)\n\n\n--num-threads NUM_THREADS\n    Number of threads to run. (default: 8)\n

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\n\n\nUMI data can be processed using the workflow based on fgbio methods. The tools can be run\nin a standalone fashion or the whole set of tools can be run using one command.
\n\nThe container components are ready for commercial/non-commercial use.\n\n### License/Terms of Use:\nUse of this software is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and the [Product-Specific Terms for NVIDIA AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).\n\n### Deployment Geography:\nGlobal\n\n### Release Date:\nNGC - 01/13/2026\n\n## Program Classes\nA GPU-accelerated software for processing UMI-tagged DNA sequencing reads to produce error-corrected consensus reads for downstream genomic analysis.\n\n## Deployment Details: \nOur accelerated fgbio tool is designed and optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware parallelism and optimized software frameworks, the toolkit achieves significantly faster genomic data processing and consensus calling times compared to standard CPU-based Java implementations
\n\n## Reference(s):\nFennell, T., Homer, N., & Fulcrum Genomics. (n.d.). fgbio: Tools for working with genomic and high throughput sequencing data, GitHub. https://github.com/fulcrumgenomics/fgbio\n\n## Container Version(s): \nv1.4.0\n\n## Ethical Considerations:\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure this container meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://app.intigriti.com/programs/nvidia/nvidiavdp/detail). \n\n# Get Help\n## Enterprise Support\nGet access to knowledge base articles and support cases or [submit a ticket](https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/).\n\n## Quick Start Run Commands\n\n### Dual Header\n```\npbrun umi_fgbio --in-fq firstInput.fastq.gz secondInput.fastq.gz \\\n --ref theReferenceFile.fasta \\\n --out-dir directoryWithOutput \\\n --umi-in-header \\\n --strategy paired\n```\n\n### Dual Read\n```\npbrun umi_fgbio --in-fq firstInput.fastq.gz secondInput.fastq.gz \\\n --ref theReferenceFile.fasta \\\n --out-dir directoryWithOutput \\\n --strategy paired \\\n --read-structures 7M1B+T 7M1B+T\n```\n\n### Dual Separate\n```\npbrun umi_fgbio --in-fq secondInput.fastq.gz fourthInput.fastq.gz firstInput.fastq.gz thirdInput.fastq.gz \\\n --ref theReferenceFile.fasta \\\n --out-dir directoryWithOutput \\\n --strategy paired \\\n --read-structures 1B+T +T 7M 7M\n```\n\n### Single Header\n```\npbrun umi_fgbio --in-fq firstInput.fastq.gz secondInput.fastq.gz \\\n --ref theReferenceFile.fasta \\\n --out-dir directoryWithOutput \\\n --umi-in-header \\\n --strategy adjacency\n```\n\n### Single Separate\n```\npbrun umi_fgbio --in-fq secondInput.fastq.gz fourthInput.fastq.gz firstInput.fastq.gz \\\n --ref theReferenceFile.fasta \\\n --out-dir directoryWithOutput \\\n --strategy adjacency \\\n --read-structures 1B+T +T 7M\n```\n\n## Input/Output file options\n\n --in-fq [IN_FQ [IN_FQ ...]]\n Path to one or more fastq files, each corresponding to\n a sub-read. Files can be in fastq or fastq.gz format.\n (default: None)\n\n **Option is required.**\n\n\n --ref REF\n Path to the reference file (default: None)\n\n **Option is required.**\n\n\n --metadata METADATA\n Path to a file containing the metadata about the\n samples. If no file is provided, output reads will be\n put into unmatched files only. (default: None)\n\n\n --out-dir OUT_DIR\n Path to the directory that will contain all of the\n generated files.\n (default: None)\n\n **Option is required.**\n\n## Pipeline Options\n\n --umi-in-header\n Specifies that UMIs are in the read header. (default:\n False)\n\n\n -L INTERVAL, --interval INTERVAL\n Interval within which to call bqsr from the input\n reads. All intervals will have a padding of 100 to get\n read records, and overlapping intervals will be\n combined. Interval files should be passed using the\n --interval-file option. This option can be used\n multiple times (e.g. \"-L chr1 -L chr2:10000 -L\n chr3:20000+ -L chr4:10000-20000\") (default: None)\n\n\n --bwa-options BWA_OPTIONS\n Pass supported bwa mem options as one string. The\n current original bwa mem supported options are -M, -Y,\n -T (e.g. --bwa-options=\"-M -Y\") (default: None)\n\n\n --no-warnings\n Suppress warning messages about system thread and\n memory usage. (default: None)\n\n\n --read-group-sm READ_GROUP_SM\n SM tag for read groups in this run. (default: None)\n\n\n --read-group-lb READ_GROUP_LB\n LB tag for read groups in this run. (default: None)\n\n\n --read-group-pl READ_GROUP_PL\n PL tag for read groups in this run. (default: None)\n\n\n --read-group-id-prefix READ_GROUP_ID_PREFIX\n Prefix for the ID and PU tags for read groups in this\n run. This prefix will be used for all pairs of fastq\n files in this run. The ID and PU tags will consist of\n this prefix, and an identifier that will be unique for\n a pair of fastq files. (default: None)\n\n\n -ip INTERVAL_PADDING, --interval-padding INTERVAL_PADDING\n Amount of padding (in base pairs) to add to each\n interval you are including. (default: None)\n\n\n --read-structures [READ_STRUCTURES [READ_STRUCTURES ...]]\n The read structure for each of the FASTQs. There must\n be one read structure per input fastq file. (default:\n None)\n\n\n --no-barcode\n Remove the requirement that input read structures must\n contain sample barcodes. (default: None)\n\n\n --out-metrics OUT_METRICS\n The file to which per-barcode metrics are written in\n the output directory. If none given, a file named\n demux_barcode_metrics.txt will be written to the\n output directory. If UMIs are in read header, no\n metrics file will be generated. (default: None)\n\n\n --num-zip-threads NUM_ZIP_THREADS\n Number of CPUs to use for zipping BAM files in a run\n (default 16 for coordinate sorts and 10 otherwise).\n (default: None)\n\n\n --num-sort-threads NUM_SORT_THREADS\n Number of CPUs to use for sorting in a run (default 10\n for coordinate sorts and 16 otherwise). (default:\n None)\n\n\n --max-records-in-ram MAX_RECORDS_IN_RAM\n Maximum number of records in RAM when using a\n queryname or template coordinate sort mode; lowering\n this number will decrease maximum memory usage.\n (default: 65000000)\n\n\n --mem-limit MEM_LIMIT\n Memory limit in GBs during sorting and postsorting. By\n default, the limit is half of the total system memory. \n (default: 1007)\n\n\n --gpuwrite\n Use one GPU to accelerate writing final BAM/CRAM.\n (default: None)\n\n\n --gpuwrite-deflate-algo GPUWRITE_DEFLATE_ALGO\n Choose the nvCOMP DEFLATE algorithm to use with\n --gpuwrite. Note these options do not correspond to CPU\n DEFLATE options. Valid options are 1, 2, and 4. Option\n 1 is fastest, while options 2 and 4 have progressively\n lower throughput but higher compression ratios. The\n default value is 1 when the user does not provide an\n input (i.e., None) (default: None)\n\n\n --gpusort\n Use GPUs to accelerate sorting and marking.\n (default: None)\n\n\n --strategy STRATEGY\n The UMI assignment strategy, which can be adjacency or\n paired. (default: )\n\n **Option is required.**\n\n\n --min-map-q MIN_MAP_Q\n Minimum mapping quality. (default: 30)\n\n\n --num-worker-threads NUM_WORKER_THREADS\n Number of threads for worker. (default: 14)\n\n\n --error-rate-pre-umi ERROR_RATE_PRE_UMI\n The Phred-scaled error rate for an error prior to the\n UMIs being integrated. (default: 45)\n\n\n --error-rate-post-umi ERROR_RATE_POST_UMI\n The Phred-scaled error rate for an error post the UMIs\n have been integrated. (default: 40)\n\n\n --min-input-base-quality MIN_INPUT_BASE_QUALITY\n Ignore bases in raw reads that have Q below this\n value. (default: 10)\n\n\n --min-consensus-base-quality MIN_CONSENSUS_BASE_QUALITY\n Mask (make ‘N’) consensus bases with quality less than\n this threshold. (default: 2)\n\n\n --min-reads MIN_READS\n The minimum number of reads to produce a consensus\n base. (default: 1)\n\n\n --out-suffixF OUT_SUFFIXF\n Output suffix used for paired reads that are first in\n pair. The suffix must end with \".gz\" (default:\n _1.fastq.gz)\n\n\n --out-suffixF2 OUT_SUFFIXF2\n Output suffix used for paired reads that are second in\n pair. The suffix must end with \".gz\" (default:\n _2.fastq.gz)\n\n\n --out-suffixO OUT_SUFFIXO\n Output suffix used for orphan/unmatched reads that are\n first in pair. The suffix must end with \".gz\". If no\n suffix is provided, these reads will be ignored\n (default: None)\n\n\n --out-suffixO2 OUT_SUFFIXO2\n Output suffix used for orphan/unmatched reads that are\n second in pair. The suffix must end with \".gz\". If no\n suffix is provided, these reads will be ignored\n (default: None)\n\n\n --out-suffixS OUT_SUFFIXS\n Output suffix used for single-end/unpaired reads. The\n suffix must end with \".gz\". If no suffix is provided,\n these reads will be ignored (default: None)\n\n\n --rg-tag RG_TAG\n Split reads into different fastq files based on the\n read group tag. Must be either PU or ID (default:\n None)\n\n\n --remove-qc-failure\n Remove reads from the output that have abstract QC\n failure. (default: None)\n\n\n --num-threads NUM_THREADS\n Number of threads to run. 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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.",5,[516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537],[400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416],{"_417":511,"_91":511,"_90":419,"_390":512},{"_417":507,"_91":507,"_90":419,"_390":508},{"_417":502,"_91":502,"_90":419,"_390":503},{"_417":498,"_91":498,"_90":419,"_390":499},{"_417":493,"_91":493,"_90":419,"_390":494},{"_417":488,"_91":488,"_90":419,"_390":489},{"_417":480,"_91":480,"_90":419,"_390":481},{"_417":472,"_91":472,"_90":419,"_390":473},{"_417":467,"_91":467,"_90":419,"_390":468},{"_417":462,"_91":462,"_90":419,"_390":463},{"_417":457,"_91":457,"_90":419,"_390":458},{"_417":452,"_91":452,"_90":419,"_390":453},{"_417":447,"_91":447,"_90":419,"_390":448},{"_417":440,"_91":440,"_90":419,"_390":441},{"_417":435,"_91":435,"_90":419,"_390":436},{"_417":428,"_91":428,"_90":419,"_390":429},{"_417":418,"_91":418,"_90":419,"_390":420},"hostName","amazon-adsystem.com","",[421,422],{"_243":427,"_424":418,"_425":26,"_90":426},{"_243":423,"_424":418,"_425":26,"_90":426},"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",[430,431],{"_243":434,"_424":428,"_425":26,"_90":433},{"_243":432,"_424":428,"_425":26,"_90":433},"IDE","This domain is owned by Doubleclick (Google). The main business activity is: Doubleclick is Googles real time bidding advertising exchange","test_cookie","bing.com",[437],{"_243":438,"_424":435,"_425":26,"_90":439},"MUID","This domain is owned by Mircosoft - it is the site for the search engine Bing.","assets.adobedtm.com",[442,443],{"_243":446,"_424":440,"_425":26,"_90":445},{"_243":444,"_424":440,"_425":26,"_90":445},"kndctr_F207D74D549850760A4C98C6_AdobeOrg_*","If you know anything about this host and its uses please add your contributions here. ","kndctr_F207D74D549850760A4C98C6_AdobeOrg_consent","tiktok.com",[449],{"_243":450,"_424":447,"_425":26,"_90":451},"_ttp","TikTok is a social media platform owned by ByteDance, known for short-form video sharing. The service is used to create and share videos, and it utilizes cookies for various purposes including advertising and analytics.","t.co",[454],{"_243":455,"_424":452,"_425":26,"_90":456},"muc_ads","This domain is owned by Twitter. 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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.","linkedin.com",[469],{"_243":470,"_424":467,"_425":26,"_90":471},"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. 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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.","_rdt_pn","www.nvidia.com","This cookie name is associated with www.mind.org.uk which is used for marketing purposes.","AMP_*","build.nvidia.com","Supports Amplitude product analytics.","_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.","investor.nvidia.com","This cookie is associated with Eventbrite and is used to deliver content tailored to the end user's interests and improve content creation. This cookie is also used for event-booking purposes.","_gat_gtag_UA_140825383_2","Google Analytics","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","catalog.ngc.nvidia.com","_uetsid","This cookie is used by Bing to determine what ads should be shown that may be relevant to the end user perusing the site. ","kndctr_F207D74D549850760A4C98C6_AdobeOrg_bc_session_id","ttcsid_XXXXXXXXXXXXXXXXXXXXCategory","This cookie name is associated with TikTok which is used to track your activity on the platform, including how you interact with their embedded services on other websites.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.","_fbp","Used by Facebook to deliver a series of advertisement products such as real time bidding from third party advertisers","_zitok","_twpid","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.","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.",[608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632],[579,580,581,582,583],{"_417":493,"_91":493,"_90":419,"_390":603},{"_417":467,"_91":467,"_90":419,"_390":598},{"_417":593,"_91":593,"_90":419,"_390":594},{"_417":588,"_91":588,"_90":419,"_390":589},{"_417":584,"_91":584,"_90":419,"_390":585},"nvidia.partners",[586],{"_243":587,"_424":584,"_425":26,"_90":461},"edge","app.hushly.com",[590],{"_243":591,"_424":588,"_425":26,"_90":592},"*CORS","This domain is associated with Hushly, a platform that provides lead conversion solutions for content marketing by using personalization and content engagement strategies.","github.com",[595],{"_243":596,"_424":593,"_425":26,"_90":597},"_octo","This domain is owned by Github. 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These cookies may store a unique ID so that our system will remember you when you return. 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