CUDA Framework Guides
Master GPU acceleration with 20+ framework guides. Each guide includes installation, code examples, performance tips, and CUDA optimization strategies.
Deep Learning Frameworks
PyTorch Python
Complete PyTorch CUDA guide. Learn GPU memory management, mixed precision training, custom CUDA kernels, and performance optimization for deep learning.
TensorFlow Python
Complete TensorFlow CUDA guide. Learn XLA compilation, mixed precision, memory growth, distributed training, and TensorRT optimization.
JAX Python
Complete JAX CUDA guide. Learn JIT compilation, automatic vectorization, parallelization with pmap, and XLA optimization for GPU computing.
Horovod Python
Complete Horovod guide. Learn distributed training with PyTorch, TensorFlow across multiple GPUs.
DeepSpeed Python
Complete DeepSpeed guide. Learn ZeRO optimization, large model training, and inference.
Megatron Python
Complete Megatron-LM guide. Learn tensor and pipeline parallelism for training GPT/BERT at scale.
Apex Python
Complete NVIDIA Apex guide. Learn AMP, distributed training utilities, and fused optimizers.
Scientific Computing Frameworks
CuPy Python
Complete CuPy guide for GPU-accelerated NumPy. Learn array operations, custom kernels, interoperability with PyTorch/TensorFlow, and CUDA optimization.
RAPIDS Python
Complete RAPIDS guide for GPU data science. Learn cuDF for DataFrames, cuML for machine learning, cuGraph for graph analytics, and CUDA optimization.
PyCUDA Python
Complete PyCUDA guide. Learn to write CUDA C kernels and call them from Python.
CUDA Compilers & Code Generation
Triton Python
Complete Triton guide for GPU kernel development. Learn to write custom CUDA kernels in Python with automatic optimization and PyTorch integration.
Numba Python
Complete Numba CUDA guide. Learn JIT compilation, CUDA kernels in Python, GPU arrays, vectorization, and performance optimization for scientific computing.
TVM Python/C++
Complete TVM guide for ML compilation. Learn AutoTVM tuning, Relay IR, CUDA code generation, operator fusion, and deployment optimization.
Numba Python
Complete Numba CUDA guide. Learn JIT compilation, GPU kernels in Python, and performance optimization.
GPU Acceleration Libraries
TensorRT Python/C++
Complete TensorRT guide for optimized inference. Learn layer fusion, precision calibration, dynamic shapes, plugins, and deployment on NVIDIA GPUs.
ONNX Runtime Python/C++
Complete ONNX Runtime guide for GPU inference. Learn CUDA execution providers, graph optimizations, quantization, and deployment across platforms.
RAPIDS Python
Complete RAPIDS guide. Learn cuDF, cuML, cuGraph for GPU-accelerated data science.
ORT Python/C++
Complete ONNX Runtime CUDA guide. Learn model optimization, TensorRT integration, and deployment.
TRT Python/C++
Complete TensorRT guide. Learn model optimization, quantization, and deployment for NVIDIA GPUs.
cuDF Python
Complete cuDF guide. Learn GPU-accelerated DataFrame operations with pandas API.
Optimize Any Framework Automatically
RightNow AI integrates with PyTorch, TensorFlow, JAX, and more to provide real-time CUDA optimization.