# Mapple: A Domain-Specific Language for Mapping Distributed Programs

arXiv: https://arxiv.org/abs/2507.17087 · HTML: https://mlsanity.com/paper/2507.17087/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2025.

## Built on by (most cited first, 1 of 1)

- [A Two-Stage GPU Kernel Tuner Combining Semantic Refactoring and Search-Based Optimization](https://mlsanity.com/paper/2601.12698/) (2026)

## Abstract (arXiv)

Optimizing parallel programs for distributed systems is a complex task, often requiring significant code modifications. Task-based programming systems improve modularity by separating performance decisions from application logic, but their mapping interfaces are low-level. We introduce Mapple, a high-level, declarative programming interface for mapping distributed applications. Mapple provides transformation primitives to resolve dimensionality mismatches between task and processor spaces, including a key primitive, decompose, that helps minimize communication volume. We implement Mapple on top of the Legion runtime by translating Mapple mappers into its low-level C++ interface. Across nine applications, including six matrix multiplication algorithms and three scientific computing workloads, Mapple reduces mapper code size by 14x and enables performance improvements of up to 1.34x over expert-written C++ mappers. In addition, the decompose primitive achieves up to 1.83x improvement over existing dimensionality-resolution heuristics.