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Slurm-Based LS-DYNA Production Computing on HPC

30 Chapters
View Course Samples Online
01
Production computing context
LS-DYNA workload characteristics, HPC cluster architecture, and the role of Slurm in simulation-driven engineering.
Productioncomputing
02
LS-DYNA solver landscape on HPC
SMP, MPP, hybrid MPI/OpenMP executables, licensing models, and version-specific deployment considerations.
LS-DYNAlandscape
03
Slurm fundamentals for LS-DYNA users
partitions, QoS, accounts, reservations, job states, and scheduler policies relevant to crash and impact simulations.
LS-DYNApartitions
04
Job submission mechanics
sbatch, srun, salloc, job scripts, environment propagation, and module loading for LS-DYNA production runs.
submissionmechanics
05
Resource request strategy
nodes, tasks, CPUs per task, memory, walltime, and their mapping to LS-DYNA MPP decomposition and memory scaling.
Resourcestrategy
06
Core-hour accounting and fair-share
tracking LS-DYNA consumption, priority factors, and cost-aware job sizing for large model runs.
Core-houraccounting
07
Input deck preparation for cluster execution
keyword files, include paths, restart d3dump, binout, and directory layout on parallel filesystems.
preparationexecution
08
Scratch and storage strategy
Lustre, GPFS, and local NVMe usage for LS-DYNA I/O, d3plot frequency, and binout output management.
strategyGPFS
09
MPI launch configuration
srun versus mpirun, process binding, CPU affinity, and fabric selection for LS-DYNA MPP scaling.
MPIconfiguration
10
Hybrid parallel tuning
MPI ranks per node, OpenMP threads, and balancing for implicit and explicit LS-DYNA analyses.
parallelMPI
11
Job script engineering
parameterized sbatch templates, job arrays for design sweeps, and dependency chains for multi-stage simulations.
parameterizedtemplates
12
Interactive and debug sessions
salloc, srun --pty, and small-scale LS-DYNA runs for deck validation before production submission.
Interactivesessions
13
Queue selection and backfill
choosing partitions for short, long, large-memory, or GPU-accelerated LS-DYNA jobs.
selectionbackfill
14
Monitoring running jobs
squeue, scontrol show job, sacct, and LS-DYNA-specific progress indicators such as d3plot and messag files.
Monitoringscontrol
15
Performance diagnostics
interpreting LS-DYNA timing summaries, MPI imbalance, I/O bottlenecks, and Slurm-reported efficiency metrics.
Performancediagnostics
16
Scaling studies
strong and weak scaling experiments for LS-DYNA MPP, identifying saturation points, and selecting optimal core counts.
experimentsLS-DYNA
17
Restart and checkpoint workflows
d3dump, d3full, and restart keyword handling under Slurm job failure or walltime limits.
checkpointworkflows
18
Failure handling
node failures, MPI aborts, license exhaustion, and Slurm requeue strategies for long LS-DYNA production jobs.
handlingfailures
19
Job arrays and parametric studies
automating LS-DYNA design-of-experiments, material sweeps, and load-case matrices with Slurm.
parametricautomating
20
Workflow orchestration
coupling LS-DYNA with pre-processors, mesh converters, and post-processors using Slurm dependencies and job steps.
Workfloworchestration
21
GPU-accelerated LS-DYNA
GRECO and GPU solver options, Slurm GRES configuration, and performance comparison with CPU MPP runs.
GPU-acceleratedLS-DYNA
22
License management
LS-DYNA license server integration, Slurm license scheduling, and avoiding over-subscription in production queues.
managementLS-DYNA
23
Data management at scale
staging input decks, archiving d3plot and binout, and lifecycle policies for LS-DYNA output on HPC storage.
managementarchiving
24
Post-processing on HPC
LS-PrePost batch mode, LS-OPT, and parallel post-processing workflows submitted through Slurm.
Post-processingHPC
25
Multi-physics and coupled analyses
LS-DYNA thermal, fluid, and electromagnetic solvers under Slurm, including co-simulation setups.
Multi-physicsanalyses
26
Benchmarking and reproducibility
standardized LS-DYNA benchmark decks, Slurm job recording, and documenting performance baselines.
Benchmarkingreproducibility
27
Security and compliance
data governance, export control, and secure Slurm job submission for proprietary LS-DYNA models.
Securitycompliance
28
Site-specific customization
Slurm prolog/epilog scripts, LS-DYNA wrappers, and integration with cluster monitoring and accounting tools.
Site-specificcustomization
29
Troubleshooting production incidents
diagnosing hung jobs, memory leaks, filesystem contention, and Slurm node drain events during LS-DYNA runs.
Troubleshootingproduction
30
Production operations capstone
designing, submitting, monitoring, and optimizing a realistic LS-DYNA crash simulation campaign on a Slurm HPC cluster.
Productionoperations