Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023); Parabricks v. 3.7.0-1

Overview

Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 as run in Table 1.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

6 evaluations · 12 results. Different protocols are not a single leaderboard.

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: DeepVariant execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: HG002 (GIAB) WGS FASTQ down-sampled to 30x, precisionFDA Truth Challenge V2	49.1 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepVariant on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-deepvariant Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 10 (DGX, GPU4, DeepVariant), column 'Time (min)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: DeepVariant execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: HG002 (GIAB) WGS FASTQ down-sampled to 30x, precisionFDA Truth Challenge V2	0.82 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepVariant on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-deepvariant Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 10 (DGX, GPU4, DeepVariant), column 'Time (h)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: HaplotypeCaller execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: HG002 (GIAB) WGS FASTQ down-sampled to 30x, precisionFDA Truth Challenge V2	39 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source HaplotypeCaller on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-haplotypecaller Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 21 (DGX, GPU4, HaplotypeCaller), column 'Time (min)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: HaplotypeCaller execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: HG002 (GIAB) WGS FASTQ down-sampled to 30x, precisionFDA Truth Challenge V2	0.65 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source HaplotypeCaller on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-haplotypecaller Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 21 (DGX, GPU4, HaplotypeCaller), column 'Time (h)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	70.4 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LoFreq on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 32 (DGX, GPU4, LoFreq), column 'Time (min)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	1.18 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LoFreq on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 32 (DGX, GPU4, LoFreq), column 'Time (h)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	23.8 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Muse on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 43 (DGX, GPU4, Muse), column 'Time (min)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	0.4 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Muse on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 43 (DGX, GPU4, Muse), column 'Time (h)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	17.2 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Mutect2 on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 54 (DGX, GPU4, Mutect2), column 'Time (min)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	0.29 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Mutect2 on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 54 (DGX, GPU4, Mutect2), column 'Time (h)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: SomaticSniper execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	65 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SomaticSniper on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-somaticsniper Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 65 (DGX, GPU4, SomaticSniper), column 'Time (min)'
Configuration: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023)	Protocol: SomaticSniper execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0	1.08 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SomaticSniper on Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100 (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-somaticsniper Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 65 (DGX, GPU4, SomaticSniper), column 'Time (h)'

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Evidence

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Sources and history

Release 2026-10-09-8cc1db47c7f9 · Record review: source checked

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Accelerating genomic workflows using NVIDIA Parabricks · Original source · BMC Bioinformatics 24:221, published 2023-05-31; PMC10230726 full-text XML

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Technical metadata and extraction receipts

Stable ID: model-execution-20261009-config-oconnell2023-dgx-gpu4

areas: dna-genomes
contexts: clinical_research
method types: conventional_pipeline
foundation model eligible: false
reported name: Parabricks 3.7.0-1, 4 A100 GPUs on NVIDIA DGX A100
hardware: description: DGX A100 node; 4 GPUs used, max memory 300 GB
source locator: Table 1 VM-type column; Methods 'GCP configuration', 'AWS configuration', 'DGX configuration'
version: Parabricks v. 3.7.0-1
protocol: Parabricks Germline Pipeline, DeepVariant Germline Pipeline, mutectcaller, somaticsniper_workflow, muse or lofreq, by protocol

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