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SYCL-accelerated H3 geospatial library

Reason this release was yanked:

new versioning scheme

Project description

H3 SYCL Bridge

Docker Prerequisites

To run the Docker images with GPU acceleration enabled (h3-turbo), you must ensure your host machine is correctly configured with NVIDIA drivers and Docker support.

Specifically, the following must be installed:

  1. NVIDIA Drivers: Ensure you have the NVIDIA GPU drivers installed on your host (compatible with CUDA 12.0+).
  2. nvidia-container-toolkit: This toolkit enables the Docker engine to access the GPU.

Installation Guide

For the NVIDIA Container Toolkit, please follow the official installation guide.

After installing the toolkit, remember to restart the Docker daemon:

sudo systemctl restart docker

You can then verify your setup by running:

docker run --rm --gpus all nvidia/cuda:12.0.0-base-ubuntu22.04 nvidia-smi

Running Automated Benchmarks via Docker

To run the automated benchmarks using Docker, you can use the provided docker-compose.benchmark.yml file. This setup automatically builds the necessary environment and executes benchmark_runner.py with GPU support enabled.

Make sure you have your H3_TURBO_LICENSE environment variable set, or pass it directly. Run the following command:

H3_TURBO_LICENSE=your_license_here docker compose -f docker-compose.benchmark.yml up --build

Note: Generated 1-month licenses are available within the Docker images published at https://hub.docker.com/repositories/cflockhart.

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