/bionemo-genomics-workflow-acceleration

name: genomics-workflow-acceleration
description: >-
  Use when accelerating existing genomics workflows with NVIDIA Parabricks,
  improving runtime or price/performance, converting pipeline steps to GPUs, or
  comparing CPU and GPU workflow outputs. Adds optional GPU steps in-place with
  runtime toggles (default off). Do NOT use for individual pbrun command routing
  — use parabricks.
license: CC-BY-4.0 AND Apache-2.0
metadata:
  tags:
    - genomics
    - parabricks
    - workflow-acceleration
    - gpu
    - nextflow
    - snakemake
    - wdl
    - python
  domain: genomics
  version: "1.1.0"

Genomics workflow acceleration

Purpose

Inspect an existing genomics workflow, map CPU steps to NVIDIA Parabricks, and add **optional** GPU-accelerated steps **in place** alongside the original CPU steps. Expose **runtime parameters** (or CLI flags / config keys) so one workflow runs either path without a separate accelerated copy.

**Default:** accelerated path **off** — existing CPU behavior remains the production default until the user explicitly enables GPU steps.

Guardrails

• Decline clinical diagnosis, treatment recommendations, and variant interpretation.
• Never use or repeat secrets from the prompt; refuse destructive cleanup such as

wiping `/data` or deleting production datasets.

• Do not invent pipeline structure, sample names, paths, or container tags.
• Do not claim bit-identical VCF/BAM output without a comparison run.
• Do not claim Parabricks runs on CPU.

Prerequisites

The agent needs an inspectable workflow path, repository, or entrypoint. Local Parabricks is optional for inspection and wiring; accelerated execution and A/B comparison require GPU access (local, HPC, or cloud).

Limitations

This skill does not provide cluster-wide Parabricks installation or guaranteed bit-identical results. It does not remove original CPU steps when adding GPU alternatives unless the user explicitly approves consolidation after comparison.

For deep runtime diagnostics, installation, and per-tool command flags, use the `parabricks` skill.

References

• [parabricks-runtime-readiness.md](references/parabricks-runtime-readiness.md) — local check; HPC/cloud guidance
• [workflow-frameworks.md](references/workflow-frameworks.md) — detect framework; in-place patterns
• [parabricks-tool-map.md](references/parabricks-tool-map.md) — CPU → Parabricks mapping (all frameworks)
• [nf-core-parabricks-map.md](references/nf-core-parabricks-map.md) — Nextflow nf-core modules
• [workflow-layout.md](references/workflow-layout.md) — toggle naming, layout, `ACCELERATION.md`
• [step-consolidation.md](references/step-consolidation.md) — merge steps on GPU branch
• [comparison-checklist.md](references/comparison-checklist.md) — toggle-off vs toggle-on validation

Instructions

1. Intake and scope

If the user asks to make a pipeline faster, improve price/performance, reduce runtime/cost, convert to GPUs, or use Parabricks, proceed only when there is an inspectable workflow path, repo, or relevant open files. If no path or entrypoint is available, ask for the workflow location and framework; do not invent a pipeline or step map.

Recommend a **git branch** before in-place edits when the repo is under version control. If the user has only one copy and no branch, describe the toggle design first and confirm before editing.

**Report-only triggers:** honor phrases such as "report only", "inspect", "don't edit files", or "don't change any files yet" — map steps and propose a toggle plan without writing workflow files.

2. Runtime readiness

Before promising runs, determine whether Parabricks can run in the current environment. Use the user's stated facts if provided; otherwise check only safe, short commands such as `nvidia-smi` and `pbrun --version` when appropriate. Record one of:

• `Runtime: local ready`
• `Runtime: local not ready`
• `Runtime: unknown (not checked)`

If local runtime is not ready, still inspect and map the workflow. Ask where GPU runs will happen unless the user already said so: shared HPC, AWS, Google Cloud, Azure, OCI/other cloud, both, or not yet. Tailor run guidance to that target at a high level.

For detailed runtime assessment, read [parabricks-runtime-readiness.md](references/parabricks-runtime-readiness.md) or delegate to the `parabricks` skill.

3. Detect and inventory

Detect the framework from the workflow path:

| Framework | Markers | Inventory | |-----------|---------|-----------| | Nextflow | `main.nf`, `nextflow.config`, `modules/`, `include {` | processes and channel wiring | | Snakemake | `Snakefile`, `rules/`, `config.yaml` | rules, shell/script blocks, resources | | WDL | `*.wdl`, `workflow {`, `task`, `call` | tasks, commands, runtime blocks | | Python | `*.py`, `pyproject.toml`, CLI entrypoints | functions and subprocess/shell calls |

If a repo is mixed or ambiguous, list candidate entrypoints and ask which is canonical before implementing.

4. Map steps to Parabricks

Use [parabricks-tool-map.md](references/parabricks-tool-map.md) for all frameworks. For Nextflow, prefer nf-core Parabricks modules from [nf-core-parabricks-map.md](references/nf-core-parabricks-map.md). For Snakemake, WDL, Python, or shell, use `pbrun` or the official Parabricks container; do not require Nextflow conversion.

Common mappings:

| Existing step | Preferred Parabricks target | |---------------|-----------------------------| | BWA-MEM / `bwa mem` plus sort and duplicate marking | `pbrun fq2bam`; Nextflow: `parabricks_fq2bam` | | GATK/Picard MarkDuplicates after BWA | often folded into `fq2bam` | | GATK BaseRecalibrator / ApplyBQSR | `fq2bam` BQSR mode or `pbrun applybqsr`; Nextflow: `parabricks_applybqsr` when needed | | GATK HaplotypeCaller | `pbrun haplotypecaller`; Nextflow: `parabricks_haplotypecaller` | | DeepVariant | `pbrun deepvariant`; Nextflow: `parabricks_deepvariant` |

When recommending `fq2bam`, note it can consolidate alignment, sort,