Accelerated NGS analysis in AI cloud (GPU cloud)
================================================

Objective
---------

Current Next Generation Sequence (NGS) analysis pipelines are run on
CPU-platforms and take a long time to complete (e.g., days). In this
session, we will discuss how to reduce the processing time of NGS
analysis pipelines using GPU-platforms.

Content
-------

-  `Introduction to concepts used in the
   lecture <GPU-NGS/01_intro.html>`__

   -  Next Generation Sequencing (NGS)
   -  Main steps of DNA sequencing
   -  Exome sequencing workflow

-  `NGS data analysis and precision genomics
   applications <GPU-NGS/02_NGS_data_analysis.html>`__

   -  Sequence data analysis
   -  Precision genomics - definition
   -  Main steps in sequence analysis workflows
   -  Precision genomics in routine clinical practice

-  `Why accelerate genomics
   workflows? <GPU-NGS/03_Why_accelarate.html>`__

   -  GPUs vs NGS

-  `CPU-only and GPU-only
   workflows <GPU-NGS/04_CPU_GPU_only.html>`__

   -  NVIDIA Clara Parabricks
   -  NAIC (Norwegian AI Cloud) workflows: CPU-only and GPU-only

-  `Evaluation of CPU-only vs GPU-only
   workflows <GPU-NGS/05_Evaluation.html>`__

   -  Testing workflows using sample data sets
   -  Processing time of CPU-only vs GPU-only workflows
   -  Performance on different NVIDIA GPU products

-  `Biological relevance of GPU-only compared to
   CPU-only <GPU-NGS/06_biological_relevance.html>`__
-  `Concerns and summary <GPU-NGS/07_summary.html>`__
-  `Hands-on experiment <GPU-NGS/08_handson.html>`__

Author/Instructor
-----------------
- Pubudu Saneth Samarakoon