ANNOUNCING NVIDIA® cuDNN – GPU Accelerated Machine Learning
NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. It emphasizes performance, ease-of-use, and low memory overhead. NVIDIA cuDNN is designed to be integrated into higher-level machine learning frameworks, such as UC Berkeley’s popular Caffe software. The simple, drop-in design allows developers to focus on designing and implementing neural net models rather than tuning for performance, while still achieving the high performance modern parallel computing hardware affords.
- Forward and backward convolution routines, tuned for NVIDIA GPUs
- Always optimized for latest NVIDIA GPU architectures
- Arbitrary dimension ordering, striding, and subregions for 4d tensors
- Forward and backward paths for common layer types (ReLU, Sigmoid, Tanh, pooling, softmax)
- Context-based API allows for easy multithreading
Product Manager – Strategic Alliances