arXiv Machine Learning September 11, 2026 By Shiyang Li, Guangyan Sun, Jinwei Tang, Yanzhi Wang, Mingyi Hong, Caiwen Ding

SparseDitto: An Agentic Sparse Compilation Framework through Architecture-Aware Synthesis on GPUs

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SparseDitto is an agentic sparse compilation framework that jointly synthesizes representation, execution schedule, and hardware mapping for sparse matrix computations on GPUs. It uses structural analysis, a learned template-ranking prior, and LLM-guided lowering to generate CUDA code, with target-GPU profiling refining the plan. The framework supports multiple operators such as SpMV, SpMM, and SpGEMM, adapts to different hardware, and achieves significant speedups over cuSPARSE, including up to 146.61× on certain matrices and 3.39× acceleration for full-batch GCN training.

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