cuDNN for Deep Learning
Convolutions and tensor ops at scale.
cuDNN for Deep Learning is a free CUDA Academy lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the CUDA Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
The Engine Behind AI Frameworks
cuDNN is NVIDIA's deep learning library. PyTorch and TensorFlow lean on it for fast convolutions and other neural net building blocks. 🧠
Why Convolutions Need Help
A convolution slides a small filter over an image, doing huge amounts of math. cuDNN implements it far faster than a naive kernel.
Start With a Handle
Like cuBLAS, cuDNN holds state in a handle you create once and reuse for every operation, then destroy at shutdown.
cudnnHandle_t h;
cudnnCreate(&h);Describe Your Data
cuDNN works through descriptors. A tensor descriptor records shape, data type, and layout so the library knows exactly what it is processing.
cudnnTensorDescriptor_t xDesc;
cudnnCreateTensorDescriptor(&xDesc);The NCHW Layout
Tensors are typically NCHW: batch, channels, height, width. Setting this layout correctly is essential for the math to line up.
cudnnSetTensor4dDescriptor(xDesc,
CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, N, C, H, W);Filters Get Their Own Descriptor
The convolution kernel weights use a separate filter descriptor describing output channels, input channels, and filter height and width.
cudnnFilterDescriptor_t wDesc;
cudnnCreateFilterDescriptor(&wDesc);Convolution Settings
A convolution descriptor stores padding, stride, and dilation, the knobs that decide how the filter sweeps across the input tensor.
Pick an Algorithm
cuDNN offers several convolution algorithms with different speed and memory tradeoffs. You query for the best one for your tensor shapes.
Reserve a Workspace
Fast algorithms need scratch space. You allocate a workspace buffer on the device whose size cuDNN tells you in advance.
size_t bytes;
cudnnGetConvolutionForwardWorkspaceSize(...,&bytes);Run the Forward Pass
cudnnConvolutionForward ties it all together: handle, descriptors, algorithm, and workspace produce the output feature map in one call.
cudnnConvolutionForward(h, &alpha, xDesc, x,
wDesc, w, convDesc, algo, ws, bytes, &beta, yDesc, y);More Than Convolutions
cuDNN also accelerates pooling, activations, and normalization, the other layers that make up a modern neural network.
Quick Check
Recall what cuDNN is built to accelerate.
Recap
You set up a handle, described tensors and filters in NCHW, chose an algorithm with a workspace, and ran a convolution forward pass. 🎓
Frequently asked questions
Is the “cuDNN for Deep Learning” lesson free?
Yes — the full text of “cuDNN for Deep Learning” is free to read here on the web, and the CUDA Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the CUDA Academy course, upgrade to CoddyKit PRO.
What will I learn in “cuDNN for Deep Learning”?
Convolutions and tensor ops at scale. You practise CUDA Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start CUDA Academy?
No prior experience is required. CUDA Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “cuDNN for Deep Learning” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this CUDA Academy lesson?
Yes. Every CUDA Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- cuBLAS GEMM Done Right
- Thrust Vectors and Transforms
- Thrust Reduce, Scan, and Sort
- cuDNN for Deep Learning