Accelerate machine learning with GPU-powered training and inference. RAPIDS, XGBoost GPU, and scikit-learn on dedicated NVIDIA hardware.
$ pip install cuml-cu12 xgboost cudf-cu12 # Running on NVIDIA Tesla P40 (24GB) Ready. _
GPU-accelerated machine learning uses NVIDIA CUDA to speed up training and predictions for classical ML algorithms. RAPIDS and XGBoost GPU can deliver 10-100x speedups over CPU-only implementations.
GPU-accelerated scikit-learn compatible algorithms.
Train gradient boosting models 10x faster on GPU.
GPU-accelerated pandas and numpy for data preprocessing.
Keep your entire ML pipeline on GPU for maximum speed.
GPU-accelerated machine learning uses NVIDIA CUDA to speed up training and predictions for classical ML algorithms. RAPIDS and XGBoost GPU can deliver 10-100x speedups over CPU-only implementations.
Deploy a GPU VPS with NVIDIA Tesla P40, SSH into your server, and run: pip install cuml-cu12 xgboost cudf-cu12. Your Machine Learning environment will be ready in minutes with full GPU acceleration.
Our GPU VPS comes with 24GB GDDR5X VRAM on the NVIDIA Tesla P40, which is sufficient for most Machine Learning workloads. For larger requirements, contact us for multi-GPU configurations.
GPU VPS is billed monthly with no lock-in contracts. You can cancel anytime. Contact us for current pricing as we finalize our GPU tier offerings.
Yes, you have full root access. Install any combination of tools alongside Machine Learning, as long as they fit within the 24GB VRAM and server resources.
Yes, all GPU VPS instances come with full root SSH access. Install any software, configure drivers, and customize the environment exactly as you need.
Deploy a dedicated NVIDIA GPU server in minutes. No reservations, no sales calls.