Deep Learning Workstations | Neural network training, large-scale data processing | GPU: NVIDIA RTX A6000 (16GB) ▲ RTX A6000 (48GB) ▲ H100 (80GB) (PCIe 4.0) | Higher GPU memory (48GB/80GB) enables complex model training (e.g., 10k+ parameters) | Advanced models may require specialized cooling infrastructure |
Rendering Workstations | 3D animation, video editing, photorealistic simulations | CPU: Intel Xeon W-2295 (18C/36T) ▲ W-3375 (28C/56T) ▲ Platinum 8380 (40C/80T) | More cores/threads boost rendering speed (e.g., 50% faster than industry standard) | Higher-tier CPUs may increase power consumption (250W+) |
Scientific Computing Workstations | Computational fluid dynamics, molecular simulations | RAM: 128GB DDR4 ▲ 256GB DDR4 ▲ 512GB DDR5 (4800 MT/s) | DDR5 memory reduces latency for iterative simulations (15% faster load times) | DDR5 requires compatible motherboards (not backward-compatible) |
General-Purpose Workstations | Office automation, multitasking, basic software development | Storage: 1TB NVMe SSD ▲ 2TB NVMe SSD ▲ 8TB NVMe RAID (2.5GB/s read) | RAID configuration ensures data redundancy (99.99% uptime) | Higher storage tiers add cost ($500+/TB) |
Customizable Workstations | Industry-specific tools (e.g., CAD, EDA, medical imaging) | Expansion: 2 PCIe slots ▲ 4 PCIe slots ▲ 8 PCIe slots + optional GPU risers | More PCIe slots allow integration of specialized cards (e.g., FPGA, high-speed I/O) | Advanced chassis design may limit desk space |
High-Performance Computing (HPC) Nodes | Cluster computing, distributed AI training, big data analytics | Networking: 1x 10GbE ▲ 2x 25GbE ▲ 4x 100GbE (InfiniBand) | 100GbE reduces latency in distributed training (2ms vs industry 20ms) | Requires HPC-grade infrastructure (e.g., dedicated switches) |