CMO.SO

CMO.SO
Cloud-Based Simulation September 2, 2025

How to Run Simulations in the Cloud: A Step-by-Step Guide with Flexcompute

By Maggie

SEO Meta Description:
Learn how to efficiently run simulations in the cloud using Flexcompute’s WebAPI and Tidy3D FDTD with our comprehensive example library.

Introduction to Cloud Integration for Simulations

In today’s fast-paced scientific and engineering landscapes, cloud integration for simulations has become a game-changer. Leveraging cloud computing allows researchers and engineers to run complex simulations without the constraints of local hardware limitations. This guide will walk you through the process of running simulations in the cloud using Flexcompute’s WebAPI and Tidy3D FDTD, offering a seamless and efficient experience.

Benefits of Cloud Integration for Simulations

Integrating simulations into the cloud offers numerous advantages:

  • Scalability: Easily scale your simulation resources based on demand.
  • Cost-Effectiveness: Pay only for the resources you use, eliminating the need for substantial upfront investments in hardware.
  • Accessibility: Access your simulations from anywhere, fostering collaboration among distributed teams.
  • Automation: Streamline the setup, execution, and monitoring of simulations through automated workflows.

Understanding Flexcompute’s WebAPI and Tidy3D FDTD

Flexcompute’s WebAPI provides a robust interface for submitting and managing simulations in the cloud. When combined with Tidy3D FDTD, a powerful finite-difference time-domain simulation tool, the platform offers unparalleled capability in running and analyzing complex simulations.

Key Features:

  • Seamless Integration: Easily integrate with existing scientific tools and frameworks.
  • Natural Language Interface: Create and manage experiments using intuitive commands.
  • Auto-Scaling: Automatically scale your simulation pipelines with cloud computing.
  • Versioning and Collaboration: Maintain version control and collaborate through shared dashboards.

Step-by-Step Guide to Running Simulations in the Cloud

1. Setting Up Your Simulation Environment

Begin by configuring your simulation parameters using Tidy3D FDTD. Define aspects such as grid specifications, mediums, structures, sources, and monitors.

import tidy3d as td
import tidy3d.web as web

td.config.logging_level = "ERROR"

# Define simulation parameters
dl = 0.05
pml = td.PML()
sim_size = [4, 4, 4]
freq0 = 3e14
fwidth = 1e13
run_time = 1 / fwidth

# Create structures, sources, and monitors
dielectric = td.Medium.from_nk(n=2, k=0, freq=freq0)
square = td.Structure(
    geometry=td.Box(center=[0, 0, 0], size=[1.5, 1.5, 1.5]),
    medium=dielectric
)
source = td.UniformCurrentSource(
    center=(-1.5, 0, 0),
    size=(0, 0.4, 0.4),
    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),
    polarization="Ex",
)
monitor = td.FieldMonitor(
    fields=["Ex", "Ey", "Ez"],
    center=(0, 0, 0),
    size=(td.inf, td.inf, 0),
    freqs=[freq0],
    name="field",
)
sim = td.Simulation(
    size=sim_size,
    grid_spec=td.GridSpec.uniform(dl),
    structures=[square],
    sources=[source],
    monitors=[monitor],
    run_time=run_time,
    boundary_spec=td.BoundarySpec.all_sides(boundary=pml),
)

2. Submitting the Simulation via WebAPI

Upload and start your simulation using Flexcompute’s WebAPI. Each simulation is assigned a unique task_id for tracking.

# Upload the simulation
task_id = web.upload(sim, task_name="webAPI", verbose=True)

# Start the simulation
web.start(task_id)

# Monitor the simulation until completion
web.monitor(task_id, verbose=True)

# Load the simulation results
sim_data = web.load(task_id, path="data/sim.hdf5", verbose=True)

3. Managing Jobs and Batches

Flexcompute’s platform allows you to manage individual jobs or handle multiple simulations through batch processing.

Single Job Management

Utilize the Job interface to estimate costs, run, and load results seamlessly.

job = web.Job(simulation=sim, task_name="job", verbose=True)
estimated_cost = web.estimate_cost(job.task_id)
sim_data = job.run(path="data/sim.hdf5")

Batch Processing

Submit multiple simulations simultaneously using the Batch object, enhancing efficiency and reducing the potential for data loss during interruptions.

# Define multiple simulations
sims = {f"sim_{i}": sim for i in range(3)}

# Initialize and run the batch
batch = web.Batch(simulations=sims, verbose=True)
batch_results = batch.run(path_dir="data")

4. Leveraging the Example Library

Flexcompute provides a comprehensive example library that serves as a valuable resource for both beginners and experienced users. These examples demonstrate various simulation setups and workflows, enabling users to quickly adapt to different simulation scenarios.

Conclusion

Cloud integration for simulations revolutionizes the way scientific research and engineering projects are conducted. By utilizing Flexcompute’s WebAPI and Tidy3D FDTD, you can run complex simulations with ease, scalability, and efficiency. This streamlined approach not only accelerates development pipelines but also fosters collaboration and innovation across diverse fields.

Ready to transform your simulation workflows? Visit Fluidize.ai today and harness the power of cloud-based simulations.

Share this:
Tags
Share