QuickByte Tutorials¶

Short, practical CARC guides for software, programming environments, and research workflows.

Conda¶

• Conda and Miniconda: introduction - What conda is, how environments work, and how to use Miniconda on CARC systems.
• Managing conda environments - Create, activate, export, and remove conda environments on CARC clusters.
• Conda channels and pip - Use conda channels (conda-forge, bioconda) and mix pip installs safely inside environments.

JupyterHub¶

• Conda environments in JupyterHub - Make your conda environments available as kernels in CARC JupyterHub.
• MPI parallelization from JupyterHub - Run MPI-parallel Python (mpi4py/ipyparallel) from CARC JupyterHub sessions.
• Parallel Python with Dask and scikit-learn - Scale scikit-learn workloads across cluster nodes from JupyterHub using Dask.

Julia¶

• Julia in JupyterHub - Register a Julia kernel and use Julia notebooks in CARC JupyterHub.

R¶

• R on CARC systems - Load R, run scripts in batch jobs, and use R interactively on CARC clusters.
• Getting R software - Available R versions and how to load them with environment modules.
• Installing R packages - Install R packages into your user library on CARC systems.
• Parallel R with the future package - Parallelize R code across cores and nodes using the future framework.
• Gurobi optimizer with R - Use the Gurobi optimization solver from R on CARC clusters.

Other programming languages¶

• Haskell at CARC - Install GHC with ghcup and build a Stack project on CARC clusters.
• Installing Perl libraries - Install Perl modules into your own home directory with cpan.

MATLAB¶

• Running MATLAB jobs - Run MATLAB non-interactively in Slurm batch jobs on CARC clusters.
• Parallel MATLAB: profile setup and batch submission - Configure a cluster profile and submit parallel MATLAB jobs.
• MATLAB Parallel Server - Use MATLAB Parallel Server to scale parpool jobs across multiple nodes.
• MATLAB on GPUs - Accelerate MATLAB computations with GPUs on CARC clusters.
• MATLAB deep learning - Train deep learning models in MATLAB using CARC GPU nodes.

Mathematica¶

• Mathematica on Easley - Derive exact beam-deflection formulas with Mathematica, then run the examples across CPUs, nodes, and a GPU on Easley.

AI and machine learning¶

• Installing deep learning packages - Install GPU-enabled deep learning frameworks (PyTorch, TensorFlow) into conda environments.
• PyTorch on CARC GPUs - Install and run GPU-enabled PyTorch on CARC clusters.
• PyTorch image classifier walkthrough - End-to-end example: train an image classifier with PyTorch on a CARC GPU node.
• TensorFlow on CARC GPUs - Install and run GPU-enabled TensorFlow on CARC clusters.
• Multi-GPU TensorFlow - Distribute TensorFlow training across multiple GPUs on a CARC node.
• AlphaFold - Run AlphaFold protein structure prediction on CARC systems.

Data, visualization, and parallel computing¶

• Apache Spark - Launch Apache Spark clusters inside Slurm allocations for large-scale data analysis.
• ParaView remote visualization - Run the ParaView server on CARC compute nodes and connect from your desktop client.
• CUDA-aware MPI - Pass GPU device pointers directly to MPI calls with the CUDA-aware OpenMPI/UCX stack, and fix the mixed-environment segfault.

Bioinformatics¶

• Variant calling with GATK - A genomics variant-calling workflow using GATK best practices on CARC systems.
• Metabarcoding analysis - Process environmental DNA metabarcoding data on CARC clusters.
• RAD-seq analysis with Stacks - Analyze restriction-site associated DNA sequencing (RAD-seq) data with Stacks.
• Genome assembly evaluation with QUAST and BUSCO - Evaluate genome assembly quality and completeness with QUAST and BUSCO.
• Coalescent simulation with msprime - Simulate genealogical histories and genome sequences with msprime.
• Demographic inference with PSMC - Infer population size history from diploid genomes using PSMC.
• Bayesian phylogenetics with BEAST - Run BEAST Bayesian evolutionary analyses on CARC clusters.

Chemistry & materials¶

• VASP materials simulation - Set up and run VASP density-functional-theory calculations on CARC clusters.
• ORCA quantum chemistry - Run ORCA quantum chemistry calculations in parallel on CARC clusters.

Computational immunology¶

• SimCov epidemiological simulation - Run the SimCov agent-based model of SARS-CoV-2 infection dynamics in lung tissue.

Astronomy¶

• Parallel CASA for radio astronomy - Run mpiCASA for parallel radio astronomy imaging on CARC clusters.

Containers¶

• Singularity / Apptainer containers - Build, pull, and run software containers on CARC clusters.

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