サプトロ イスティアサ

Train neural networks across multiple servers. Use techniques such as activation checkpointing, gradient accumulation, and various forms of model parallelism to overcome the challenges associated with large-model memory footprint. Capture and understand training performance characteristics to optimize model architecture. Deploy very large multi-GPU models to production using NVIDIA Triton™ Inference Server.