Simulation Cluster: Physics Engine and Monte Carlo HPC
Large-scale MPI cluster for particle physics, climate modeling, and nuclear simulation.
Scientific simulation workloads lead the category making the highest demands on computing infrastructure. In fields such as Monte Carlo methods, particle physics simulations, and climate modeling, a single computational task requires the concurrent execution of thousands of independent experiments, or very tightly MPI-coupled large domain decompositions. An HPC cluster specially designed to carry workloads at this scale is the core infrastructure component of research.
Why Is HPC Essential for Simulation?
Three fundamental characteristics distinguish scientific simulation workloads from standard servers:
Scale: A realistic nuclear reactor safety analysis or global climate model consumes memory and processor resources far beyond what a single compute node can provide. A Geant4 simulation tracking 100 million particles can run for days on 512–2,048 cores.
Statistical precision: In Monte Carlo methods, the confidence interval of the result is inversely proportional to the square root of the sample count. Halving the error margin requires four times the computation. This translates into batch workloads expressed in tens of thousands of simulations.
Data integrity: In regulated domains such as nuclear safety or clinical dosimetry, simulation outputs must be stored with auditable provenance. For research institutions operating in Turkey, KVKK-compliant, Turkey-located infrastructure is the safest way to meet this requirement.
Core Workload Categories
Monte Carlo Simulations
The Monte Carlo method produces numerical results via probabilistic sampling in problems where deterministic analytical solutions are impossible or insufficient.
- Geant4: Particle-matter interaction simulation framework from CERN. Nuclear and radiological medicine, detector design, space radiation protection studies. Scales to thousands of cores with MPI parallel job partitioning.
- MCNP / OpenMC: Neutron and photon transport. Nuclear reactor analyses, radiation shielding, nuclear safety assessments.
- FLUKA: Particle physics experiment infrastructure design and radiation dose calculation; the operational tool of institutions like CERN and SLAC.
- EGS (Electron Gamma Shower): Medical physics and radiotherapy plan validation.
Particle Physics Simulations
In large particle collider experiments (ATLAS, CMS, etc.), simulation data is produced in volumes exceeding real event data.
- Geant4 + ROOT + Pythia: Detector response simulation, signal/background separation, collision event generation.
- PYTHIA / HERWIG / SHERPA: High-energy particle scattering event generators; standard tools for LHC experiments.
- MadGraph / MadEvent: New physics model cross-section calculations.
These workloads have high parallelization efficiency; when independent event sets are run simultaneously on separate cores, linear speedup is achieved.
Climate and Atmosphere Modeling
- WRF (Weather Research and Forecasting): Regional weather and climate simulation. A 72-hour forecast run at 1 km resolution over Turkey’s scale takes 4–8 hours on 128–512 cores.
- NEMO / MOM6: Ocean circulation models; MPI coupling is intensive at high resolution.
- CESM / E3SM: Full system climate models combining atmosphere, ocean, land surface, and ice cover.
- OpenIFS (ECMWF): Numerical weather prediction; as resolution increases, computational cost grows cubically.
Nuclear and Radiation Safety Calculations
Deterministic and stochastic methods are used together in nuclear reactor design and safety analyses.
- SERPENT 2: Monte Carlo reactor physics; criticality calculation, neutron spectrum, fuel burnup.
- SCALE (ORNL): Reactor safety, criticality safety, and radiation protection package.
- RELAP / TRACE: Thermal-hydraulic transient analyses.
- CODE_BRIGHT / TOUGH+: Geomechanical and multiphase flow; nuclear waste repository analysis.
Simulation Cluster Configuration
Scientific simulation workloads require both high core counts and good network bandwidth. Mevasis reference architecture is given below:
Management / Login Nodes (2×, HA pair)
├── CPU Compute Nodes (32–256 units)
│ └── 2× AMD EPYC 9654 (96 cores/node, 384 GB DDR5)
│ — Monte Carlo, MPI CFD, climate model
├── High-Memory Nodes (4–8 units)
│ └── 2× EPYC + 1.5–3 TB DDR5
│ — MCNP/OpenMC large geometry, WRF high resolution
├── GPU Acceleration Nodes (optional, 4–16 units)
│ └── 2× AMD EPYC + 4× NVIDIA H100 SXM5
│ — Geant4 GPU port, ML-based emulator
└── Parallel File System
└── BeeGFS 7.x, NVMe + SAS layered, ≥20 GB/s read
Network: InfiniBand HDR200 (200 Gbit/s), fat-tree topology — Monte Carlo job array communication must be low-latency.
Software and Workload Comparison Table
| Software | Category | MPI Support | GPU Support | Typical Cores |
|---|---|---|---|---|
| Geant4 | Particle physics | Yes (MT + MPI) | In development | 64–4,096 |
| OpenMC | Nuclear Monte Carlo | Yes | Yes (CUDA) | 128–2,048 |
| MCNP 6.3 | Neutron transport | Yes | No | 64–2,048 |
| FLUKA | High-energy physics | Yes | No | 64–1,024 |
| WRF 4.x | Climate / Weather forecast | Yes | Yes (GPU build) | 128–2,048 |
| SERPENT 2 | Reactor physics MC | Yes | No | 64–1,024 |
| PYTHIA 8 | Event generator | No (job array) | No | N×1 |
| ROOT | Data analysis | Parallel I/O | No | 32–512 |
Parallelization Strategies
Job Array (Completely Independent)
The large majority of Monte Carlo workloads are embarrassingly parallel: each job runs the same geometry with a different random seed. Submitting thousands of tasks simultaneously is possible with SLURM job array:
#SBATCH --array=1-10000
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
srun geant4_sim --seed=$SLURM_ARRAY_TASK_ID --events=100000
This model keeps core efficiency at 98%+ since communication overhead is nearly zero.
Domain-Decomposed MPI (Tightly Coupled)
Climate models such as WRF, CESM, and NEMO divide the simulation domain among MPI processes. At each step, boundary values of neighboring regions are exchanged (halo exchange). This traffic is directly dependent on InfiniBand connection latency:
- Ethernet (25G): 4 µs halo exchange latency
- InfiniBand HDR (200G): 0.6 µs — 20–35% faster on the same workload
Hybrid Model (Threaded + MPI)
Modern software (Geant4 10+, OpenMC, SCALE) combines intra-node thread parallelism (OpenMP/native threads) with MPI. Typical SLURM configuration:
#SBATCH --nodes=16
#SBATCH --ntasks-per-node=2 # MPI processes/node
#SBATCH --cpus-per-task=48 # OpenMP threads
export OMP_NUM_THREADS=48
srun --mpi=pmi2 openmc -s 2
Data Security and Compliance
Defense applications, nuclear safety assessments, and clinical dosimetry studies require strict data management policies.
KVKK Compliance: Files containing personal data in the research process (clinical patient plans, experimenter identities) must be processed and stored within Turkey’s borders. Mevasis installs all infrastructure in Turkey-located data centers or at the customer’s own facility.
Audit Trail: For nuclear safety analyses, simulation input files, software versions, output summaries, and run conditions are stored as immutable logs. SLURM job accounting and audit systems meet this requirement.
Access Control: For sensitive geometry and material data (nuclear plant design parameters, defense ballistic models), node-level network isolation and role-based file system access are applied.
Mevasis Simulation HPC Services
Mevasis provides specialized simulation infrastructure design, installation, and management services for research and engineering institutions:
- Workload analysis and sizing: Your existing Geant4, WRF, or OpenMC workloads are profiled to determine the correct core count, memory, and storage sizing.
- Turnkey cluster installation: Hardware procurement, InfiniBand network design, SLURM + OpenPBS configuration, BeeGFS parallel file system installation.
- Software stack installation: Geant4, ROOT, OpenMC, WRF, MCNP, SCALE, SERPENT 2, and their dependencies compiled and optimized.
- HPC Rental: Project-specific computing capacity — without fixed infrastructure investment.
- HPC Consulting: MPI parameter optimization, SLURM policy design, performance bottleneck analysis.
- Managed HPC Service: Full support including 24/7 monitoring, backup, and update management.
Consult our technical team for your simulation cluster needs: Contact us →
Frequently Asked Questions
What is the most effective way to accelerate Geant4 simulations? For Geant4, the highest return is increasing core count with job array; linear scaling with event count is achieved. Geant4 MT build with intra-node thread parallelism can provide an additional 15–25% gain. The GPU port (G4HepEm) for certain physics processes is in the research phase.
Is InfiniBand required for WRF? For small-domain (e.g., single province) low-resolution runs, 25G Ethernet may suffice. InfiniBand HDR is recommended for 1 km or finer resolution regional modeling at Turkey scale; halo exchange latency directly determines solution time.
Is there a risk of random number repetition in Monte Carlo simulations? Yes, it is critical that seed values do not collide in job arrays. For Geant4 and OpenMC, the SLURM task ID is linked to the seed parameter so each job uses a unique random sequence. Mevasis simulation templates handle this automatically.
Can nuclear computation data be processed in the cloud? Detailed geometry and material databases used in criticality analyses and reactor safety assessments may fall under export control regulations (EAR, Nuclear Suppliers Group guidelines). Turkey-based on-premise or Mevasis managed infrastructure is the only option where this risk is eliminated.
How high can the SLURM job array limit be set? The default SLURM configuration has MaxArraySize of 1,001; this parameter is increased up to 100,000 in Mevasis installations based on the research team’s needs. Monte Carlo campaigns containing 10,000+ jobs are routinely managed.