SolidWorks Visualize Taking Forever? Here is a Cloud-Based Alternative

You press "Render," your laptop fans spin up to jet-engine volume, and you wait. 20 minutes. 40 minutes. An hour. Meanwhile, you can't open email without lag, your battery drains, and your calendar reminder pops up: the client call is in 15 minutes.

This is the reality of local rendering for most engineers. But it doesn't have to be.

Part 1: Why Local Rendering is Slow

The Physics of Path Tracing

Modern rendering engines (SolidWorks Visualize, KeyShot, Blender Cycles) use path tracing—a technique that simulates light bouncing through a scene. For each pixel in the final image, the engine:

1. Shoots a ray from the camera through that pixel into the scene
2. Calculates where it hits a surface
3. Bounces the ray based on material properties (reflection, refraction)
4. Repeats steps 2-3 until the ray exits the scene or is absorbed
5. Averages thousands of these rays ("samples") to reduce noise

For a 4K image (8.3 million pixels) with 256 samples per pixel, that's 2.1 billion ray calculations—per frame.

The Hardware Bottleneck

Your laptop's GPU (or CPU) has finite compute power. Here's how common hardware handles a moderately complex render (500-part assembly, 1080p, 128 samples):

Benchmark Test Setup: 500-part gearbox assembly (50MB STEP), 1080p output, 128 samples per pixel. TFLOPS = Trillion floating-point operations per second. RTX specs verified via TechPowerUp; Apple specs via official documentation.

Part 2: What is Cloud Rendering?

Cloud rendering moves the compute-intensive work from your machine to remote servers. The architecture works like this:

1. Upload: Your browser sends the CAD file (or scene description) to the cloud.
2. Process: Cloud servers tessellate geometry, load materials, and set up the scene.
3. Render: A cluster of GPUs path-traces in parallel—each GPU handles a portion of the image.
4. Stream: The final image (or live viewport) is streamed back to your browser.

Why Parallelism Wins

Path tracing is "embarrassingly parallel"—each pixel is independent. If you have 8 GPUs, you can render 8x faster (in theory). Cloud providers have thousands of GPUs available. The ceiling isn't your hardware; it's your provider's capacity.

Part 3: Tradeoffs and Considerations

When to Use Local

• You own a high-end workstation and render infrequently
• Data security policies prohibit cloud uploads
• You're in an environment without reliable internet

When to Use Cloud

• You render frequently and time-to-output matters
• Your hardware is a laptop or Mac without discrete GPU
• Multiple team members share rendering workload
• You need to iterate quickly during stakeholder calls

Part 4: Cost Comparison Over 1 Year

Let's model costs for an engineer who renders 10 images per week:

Wait—Reific looks more expensive? Here's what the table doesn't capture:

• Time savings: 10 renders × 30 min each × 52 weeks = 260 hours of waiting. At $75/hour, that's $19,500 in opportunity cost.
• Native CAD: Generic cloud renderers still require mesh conversion. Reific doesn't.
• Collaboration: Shareable links, commenting, version history—included.

How Reific's Cloud Works

Our infrastructure is specifically optimized for CAD data:

• NURBS-native ingestion: We don't triangulate on your machine—we do it server-side with industrial kernels.
• Progressive streaming: You see a preview in under 3 seconds, with quality ramping up to final.
• Smart caching: Repeated renders of the same model skip geometry processing.
• Enterprise options: Private compute, zero-retention processing for IP-sensitive work.

FAQ

Further Reading

• Rendering on a MacBook Air — Yes, it's finally possible
• KeyShot vs Blender vs Reific — Full comparison guide