The Two Best Customization Methods to Maximize BIM Efficiency
XASUN custom workstations and servers are designed by analyzing industry-specific software features and leveraging the latest IT technologies. The result is highly reliable, high-performance, cost-effective graphics workstations and storage servers tailored specifically for designers’ needs.
This solution focuses on delivering a practical, budget-friendly, and dependable XASUN graphics workstation and storage server setup. It is based on extensive research into building CAD, landscape design, model file storage, and sharing within the BIM industry.
The Optimal Tools for Enhancing BIM Efficiency Through Customized Workstations and Servers
BIM, or Building Information Modeling, is rapidly replacing CAD in design agencies worldwide. Just as CAD revolutionized hand-drawn plans, BIM marks a significant leap forward from CAD. Within architectural design, BIM is essential for maintaining competitiveness and technological advantage. High-performance graphic workstations are critical throughout BIM workflows.
However, many interior designers, landscape architects, and furniture designers encounter difficulties running Revit during model construction—especially with large, integrated models. This is often due to a mismatch between application software demands and hardware capabilities.
Clients require graphic workstations capable of efficiently running BIM software. Achieving this demands expertise from hardware specialists or skilled engineers who understand industry software characteristics and computing needs. They can recommend optimal workstation configurations that prevent hardware bottlenecks, ensuring the architectural design software runs smoothly. This approach maximizes equipment lifespan, reducing premature obsolescence caused by IT upgrades and replacements.
To achieve this, experts must deeply analyze BIM software features and industry applications, then provide effective hardware configurations to ensure Revit and similar design software perform flawlessly and efficiently.
BIM Applications and Graphic Workstation Solutions
When creating architectural and landscape models in BIM, tasks such as creating, copying, scaling, moving, rotating, rendering, and saving models reflect the workstation’s processing capabilities. Understanding CPU floating-point operations, GPU graphics processing, hard drive read/write speeds, network storage server capacity, and IO data transfers between storage and network ports is crucial to identifying system performance and bottlenecks.
Revit Software Processing and Workstation Hardware Requirements
As BIM systems become more complex and accurate, model file sizes can range from 10MB up to 2GB. In this context, the workstation’s memory and CPU are paramount, followed by GPU performance, virtual memory management, and hard drive IO speeds—all of which significantly impact software performance.
The Process of Loading Model Files into Memory and Saving to Disk
Opening a model file involves reading data from the hard drive, then decompressing and storing 3D graphics data in memory for editing. Typically, only one CPU core handles decompression and writing compressed data back to the hard drive.
If the system memory is insufficient, parts of the architectural model data spill over into virtual memory, slowing or halting editing. Usually, the memory footprint of a model file is about 20 times the original file size.
Editing the Building Model
Once loaded into memory, designers interactively edit the model—modifying, moving, transforming, and displaying updates in real time. The GPU is responsible for rendering these changes, reflecting its ability to process and display graphics data smoothly. GPU performance and model capacity support are critical here.
CPU interaction handles numerous related operations, including rendering 3D images. Revit supports multi-CPU and multi-core processing for rendering tasks, so higher CPU frequency and core count lead to better performance. Recommended CPUs are based on Intel server-grade specs, such as 4-core Xeon E3 or 4-core/6-core Xeon 5600 series, which are currently among the most advanced. The typical CPU-to-memory ratio is 1:4.
GPU Recommendations
Software vendors recommend graphics cards supporting DirectX 9.0 or higher. Professional GPUs primarily use OpenGL, and Revit supports Windows-based gaming cards. Nvidia dominates the market, followed by ATI. We mainly utilize Nvidia GeForce cards. If ATI is considered, performance should be compared against GeForce equivalents. Current Nvidia GeForce cards use the Fermi architecture, including GTX 550, GTX 560, GTX 580, and GTX 590.
The Importance of Hard Drives
Hard drives are often underestimated by users who view them merely as storage devices. However, slow model movement and scaling during editing often result from slow data exchange with virtual memory, which degrades user experience. Therefore, understanding hard drive read/write performance is vital for high-end applications.
Large, complex models require fast disk read/write speeds and efficient virtual memory handling. Improving RAID configurations can help. Although SSDs offer strong performance, professional workstations need enterprise-level drives.
Currently, Intel’s enterprise-level SSDs (like the X25-E with 64MB cache) are expensive and limited in capacity and performance (~250-270MB/s). Laptop-grade SSDs have shorter lifespans compared to enterprise SSDs—often over ten times shorter.
High-end setups often use 8 SAS 15K+ drives with SAS2-RAID 5 arrays, delivering read/write speeds of approximately 1400MB/s and 900MB/s, respectively. When memory is sufficient, virtual memory can be assigned to virtual hard drives, significantly boosting performance—depending on software support.
Display Solutions for Increasingly Large Models
As building models grow, higher display resolutions enhance design precision. Typical single displays offer 1920 × 1080 resolution, while professional monitors provide up to 2560 × 1600. Multi-screen setups (2×1, 3×1, 2×2, etc.) further increase display area. However, higher resolution demands greater GPU processing power, increasing hardware requirements.
Building Model Classification and Workstation Configuration
Model file sizes vary widely, necessitating different performance levels from graphics workstations. Based on model size and complexity, workstation capacity and computational power requirements differ significantly and should be tailored accordingly.
Must log in before commenting!
Sign Up