标题： MCFuser：高性能和快速融合的内存绑定计算密集型操作符 显示英文标题

标题： MCFuser: High-Performance and Rapid Fusion of Memory-Bound Compute-Intensive Operators

摘要： 操作符融合是一种关键的技术，用于提高数据局部性并缓解GPU内存带宽压力，但由于计算吞吐量饱和，通常无法扩展到多个计算密集型操作符的融合。 然而，张量维度大小的动态性可能导致这些操作符变为内存受限，从而需要生成融合内核，这一任务受到融合策略搜索空间有限、冗余内存访问和长时间调优的阻碍，导致性能不佳和部署效率低下。 我们引入了MCFuser，这是一个开创性的框架，旨在通过为所谓的内存受限计算密集型（MBCI）操作符链生成高性能融合内核来克服这些障碍。 利用高级分块表达式来界定一个全面的搜索空间，并结合有向无环图（DAG）分析以消除冗余内存访问，MCFuser简化了内核优化。 通过实施修剪搜索空间的指导方针，并结合分析性能模型与启发式搜索，MCFuser不仅显著加速了调优过程，还表现出卓越的性能。 在NVIDIA A100和RTX3080 GPU上与领先的编译器Ansor进行基准测试，MCFuser在内核性能方面实现了高达5.9倍的加速，并在减少调优时间超过70倍的同时超越了其他基线，展示了其敏捷性。 显示英文摘要

摘要： Operator fusion, a key technique to improve data locality and alleviate GPU memory bandwidth pressure, often fails to extend to the fusion of multiple compute-intensive operators due to saturated computation throughput. However, the dynamicity of tensor dimension sizes could potentially lead to these operators becoming memory-bound, necessitating the generation of fused kernels, a task hindered by limited search spaces for fusion strategies, redundant memory access, and prolonged tuning time, leading to sub-optimal performance and inefficient deployment. We introduce MCFuser, a pioneering framework designed to overcome these obstacles by generating high-performance fused kernels for what we define as memory-bound compute-intensive (MBCI) operator chains. Leveraging high-level tiling expressions to delineate a comprehensive search space, coupled with Directed Acyclic Graph (DAG) analysis to eliminate redundant memory accesses, MCFuser streamlines kernel optimization. By implementing guidelines to prune the search space and incorporating an analytical performance model with a heuristic search, MCFuser not only significantly accelerates the tuning process but also demonstrates superior performance. Benchmarked against leading compilers like Ansor on NVIDIA A100 and RTX3080 GPUs, MCFuser achieves up to a 5.9x speedup in kernel performance and outpaces other baselines while reducing tuning time by over 70-fold, showcasing its agility.