SingleGPU

SingleGPU is a term used to describe a computing configuration that uses a single graphics processing unit (GPU) to handle graphics rendering and, in many cases, general purpose computation. In consumer and professional systems, single-GPU setups are common for gaming desktops, creator workstations, and certain servers where workloads fit on one card. Some laptops rely on a single discrete GPU while using integrated graphics for low-power tasks, with the discrete GPU often activated for demanding applications.

Typical workloads on a single-GPU system include video games at high settings, 3D rendering, CAD, and smaller-scale machine learning or data processing tasks. For large neural networks or high-throughput rendering pipelines, single-GPU configurations may become a bottleneck, and multi-GPU configurations or accelerator clusters are preferred to achieve higher throughput.

Performance characteristics: the total compute and memory bandwidth are limited to the capabilities of one GPU and its VRAM. Memory capacity, GPU clock speeds, and PCIe bandwidth can be limiting factors, and software must manage data transfer efficiently to avoid bottlenecks. Software support includes APIs like CUDA (NVIDIA), ROCm (AMD), and OpenCL, plus framework libraries for ML and rendering. Driver stability and compatibility can influence performance and features on a single-GPU system.

Advantages of single-GPU setups include lower cost, simpler power and cooling requirements, easier software setup, and reduced development complexity. They also avoid synchronization overhead and driver conflicts that can occur with multiple GPUs. Limitations include limited performance scaling, potential memory constraints, and a lack of fault tolerance that comes with distributed GPU configurations.