AI Accelerators Course

Hands-on programming labs for exploring how classic deep-learning primitives run on different accelerator backends.

Repository Layout

• tasks/01-softmax-cpu/ - CPU reference implementation of softmax with a runnable example target.
• tasks/02-softmax-cuda/ - CUDA port of the softmax kernel plus a simple harness.
• tasks/03-matmul-cuda/ - CUDA matrix multiplication exercise and demo driver.
• tasks/04-softmax-ascend/ - Softmax operators targeting Huawei Ascend hardware.
• tasks/05-mixed-ascend/ - Mixed matrix multiplication + Softmax Ascend exercises building on the softmax work.

Build & Run

All tasks are optional CMake targets controlled by feature flags:

cmake -S . -B build -DENABLE_CPU=ON -DENABLE_CUDA=ON -DENABLE_ASCEND=OFF
cmake --build build

Each task exposes its sample executable under tasks/<task-name>/<your_id>. After building, binaries live in build/tasks/<task-name>/<your_id>/. Toggle the ENABLE_* switches to limit the build to the environments available on your machine.