Advent of Code 2025

This year, I did each day in a different programming model targeting GPU execution!

Solutions

| Day | Programming Model | Run Command | |:----|:------------------|:------------| | 01 | CuTe | uv run python day01.py | | 02 | cupy | uv run python day02.py | | 03 | warp | uv run python day03.py | | 04 | cudf | uv run --with "cudf-cu13=25.10.*" python day04.py | | 05 | cuda.cccl | uv run python day05.py | | 06 | numba-cuda | uv run python day06.py | | 07 | C++ Standard Parallelism | ./build/day07 (after building) | | 08 | CUDA with CCCL | ./build/day08 (after building) | | 09 | OpenMP | ./build/day09 (after building) | | 10 | CUDA | ./build/day10 (after building) | | 11 | C++ std::execution | ./build/day11 (after building) | | 12 | OpenACC | ./build/day12 (after building) |

I also did Day 04 in OpenACC and Day 12 in cudf.

Dependencies

• uv with Python >= 3.13 installed
• CUDA >= 13.0
• NVIDIA HPC SDK >= 2025.09
• NVIDIA GPU with driver supporting CUDA 13
• CMake >= 4.0

Building

Run/modify ./build_all.sh as you see fit:

./build_all.sh

Running

Assuming you have all prerequisites in place and you already compiled the C++ solutions, simply invoke:

./run_all.sh