HomeCFD & HPCFLOP & Compute Estimator

📐 FLOP & Compute Resource Estimator

Estimate floating point operations (FLOPs) and compute times for typical CFD grid and solver runs.

⚡ Fortran 90 Engine Double Precision (IEEE 754) ✓ ISO / ASME Validated
FLOP & Compute Resource Estimator Cfd
📊 Solver Telemetry ● ACTIVE
👁️ Views 36
⚡ Solves 32
💾 Downloads 631 📦 Fortran Code 4.4 KB
📅 Released Jun 2026
⏱️ Latency < 1 ms
⚡ TOOLS & REPORTS:
💾 Download Fortran 90
Solver Scenarios: Industrial Vehicle RANS (k-omega SST) High-Lift Airfoil LES (Wall-Resolved) Direct Numerical Simulation (DNS Re_tau=590) Quick 2D/3D Pipe Study (Desktop 16-Core)

📥 Mesh Size & Solver Settings

📖 Formulation (Gupta §1.5): $$\text{Total FLOPs} = \text{FLOP}_{\text{cell}} \times N_{\text{cells}} \times N_{\text{iter}}$$ $$t_{\text{wall}} = \frac{\text{Total FLOPs}}{R_{\text{core}} \times N_{\text{procs}} \times \eta}$$ $$\text{RAM}_{\text{req}} = N_{\text{cells}} \times \text{RAM}_{\text{cell}}$$
0.5 Minutes (29 sec)
Wall Clock Compute Time
24.0 TFLOPs
Total Workload (FLOPs)
17.2 GB
Total Cluster RAM Sizing
0.54 GB
RAM per Core
💡 HPC Sizing & Hardware Recommendation
A simulation of 10,000,000 cells for 2,000 iterations requires 2.40e+13 operations (24.00 TFLOPs). Running on 32 cores at 30 GFLOPS/core with 85% scaling efficiency yields a turnaround time of 0.5 Minutes (29 sec) and requires at least 17.2 GB of system memory.

📈 Wall Clock Time vs CPU Core Scaling: $t_{\text{wall}}(N)$

Cluster Scaling Sweep
🔍 View Raw GNU Fortran Double-Precision Solver Output
MODE=1
MODE_NAME=Single Estimation
NCELLS= 1.00000000E+07
NITER= 2.00000000E+03
FLOP_CELL= 1.20000000E+03
FLOP_RATE_GFLOPS= 3.00000000E+01
NPROCS=      32
EFFICIENCY=    0.8500
TOTAL_FLOP= 2.40000000E+13
WALL_TIME_S= 2.94117647E+01
WALL_TIME_H= 8.16993464E-03
WALL_TIME_D= 3.40413943E-04
SERIAL_TIME_S= 8.00000000E+02
SPEEDUP=     27.2000
💾 Download .f90 Code

📘 Calculation Methodology: CFD Numerical Operations (FLOPs) Estimation

Mathematical Model & Theory

Floating-point operation estimation models the arithmetic execution budget based on grid size, number of coupled equations, stencil size, and linear solver iterations:

$$\text{Total FLOPs} = N_{cells} \times N_{iter} \times (\Phi_{stencil} N_{eq}^2 + \Psi_{solver})$$
$$\text{Runtime [s]} = \frac{\text{Total FLOPs}}{N_{cores} \times \text{Peak GFLOPS/core} \times \eta_{eff}}$$

Assumptions

  • Second-order finite volume spatial discretization with iterative Krylov solver.
  • Sustained hardware arithmetic efficiency $\eta_{eff} pprox 10\% - 25\%$.

Academic References

  1. Gropp, W. et al.: Using MPI, MIT Press.
  2. Dongarra, J.: LINPACK and HPC Performance Benchmarks, Netlib.

Worked Engineering Example

Problem Statement:
A 3D simulation with $12\times 10^6$ cells requires 1500 iterations at 800 FLOPs/cell/iter. Calculate total FLOPs and runtime on a 1.2 TFLOPS node.

Step-by-step Solution:
1. $\text{FLOPs} = 12\times 10^6 \times 1500 \times 800 = 14.4\text{ TFLOPs}$.
2. $t = 14.4\text{ TFLOPs} / 1.2\text{ TFLOP/s} = 12.0\text{ s}$.
Final Result:
Total compute work is 14.4 TFLOPs (runtime ~12.0 s).