GPUs & Accelerators covers discrete graphics processing units, AI inference and training cards, FPGA accelerators, and purpose-built compute accelerators designed for installation in servers, workstations, and edge appliances. Products range from single-slot, low-profile inference cards drawing under 75 W with no auxiliary power requirement, to multi-slot flagship training GPUs exceeding 700 W that require high-amperage PCIe power connectors and high-airflow chassis support. Key buying considerations include PCIe generation and lane count (Gen 4 ×16 vs. Gen 5 ×16), on-board VRAM capacity and bus width, thermal design (active vs. passive cooling for dense GPU servers), NVLink or proprietary interconnect support for multi-GPU scaling, and driver ecosystem compatibility with your target framework—CUDA, ROCm, or OpenCL.

Common use cases include large language model training and fine-tuning, real-time video analytics and computer vision inference at the edge, scientific simulation, 3D rendering for digital content production, and financial modeling workloads requiring high FP64 throughput. Data center operators, AI research teams, broadcast facilities, and engineering departments running CAD or CFD simulations are the primary buyers.