EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Lobsters·Aug 13·5 min read
How should Futhark expose irregular arrays to the programmer?
TL;DR
Futhark has introduced features like flattening nonuniform data parallelism and recursive functions, enhancing GPU code generation. These improvements optimize parallelism without altering program semantics.
✦ Why It Matters
Explore Futhark's new features to enhance your GPU programming and improve performance in parallel computing tasks.
Key Takeaways
- Utilize flatmap to handle irregular arrays in Futhark.
- Implement recursive algorithms like quicksort using flatmap.
- Leverage shape vectors for dynamic array sizes in functions.
- Evaluate performance impacts of flatmap in your applications.
How It Works
Flatmap allows functions to return arrays of varying sizes, enabling the processing of irregular data structures. It accepts an array of sizes and a function that generates arrays based on these sizes, returning a concatenated result.
This mechanism allows for parallel execution of recursive calls, enhancing performance in divide-and-conquer algorithms.