The constantly increasing compute throughput of NVIDIA GPUs presents a new opportunity for optimizing vision AI workloads: keeping the hardware fed with data….
The constantly increasing compute throughput of NVIDIA GPUs presents a new opportunity for optimizing vision AI workloads: keeping the hardware fed with data. As GPU performance continues to scale, traditional data pipeline stages, such as I/O from storage, host-to-device data transfers (PCIe), and CPU-bound processing like decoding and resizing, don’t always keep pace. This disparity can create a…
