A low-latency and energy-efficient tensor algebra accelerator design must optimize how data movement and operations are scheduled (i.e., mapped) in the accelerator architecture. A key mapping optimization is fusion, meaning holding data on-chip between computation steps in the workload, which has been shown to reduce energy and latency by reducing expensive off-chip data movement. However, the optimal fusion choice depends on the workload and workload shape, and a mapper, which searches for the optimal mapping, can improve energy and latency significantly. However, prior mappers cannot find optimal mappings with fusion (i.e., fused mappings) in a feasible runtime because the number of fused mappings to search increases exponentially with the number of computation steps in the workload. In this paper, we introduce the Fast and Fusiest Mapper (FFM), a mapper to quickly find optimal mappings in a comprehensive fused mapspace for tensor algebra workloads. FFM shrinks the search space by pruning subsets of mappings (i.e., partial mappings) that are shown to never be a part of optimal mappings, quickly eliminating all suboptimal mappings containing those partial mappings. Then FFM joins partial mappings to construct optimal fused mappings. Using FFM, we demonstrate an energy-delay-product (EDP) reduction by up to $1.8\times$ compared to TransFusion, a state-of-the-art accelerator with hand-optimized fusion. Moreover, we show that FFM finds mappings orders of magnitude faster ($>10,000\times$) than prior automated mappers TileFlow and SET, and given the same runtime, reduces EDP by $>2\times$.

翻译：低延迟和高效能的张量代数加速器设计必须优化数据移动与操作在加速器架构中的调度方式（即映射）。一项关键的映射优化是融合，即在工作负载的计算步骤之间将数据保留在芯片上，这已被证明可通过减少昂贵的片外数据移动来降低能耗与延迟。然而，最优融合选择取决于工作负载及其形状，而搜索最优映射的映射器能显著提升能效与延迟性能。但现有映射器无法在可行运行时间内找到带融合的最优映射（即融合映射），因为需搜索的融合映射数量随工作负载计算步骤数呈指数增长。本文提出快速且最优融合映射器（FFM），该映射器可快速在张量代数工作负载的全面融合映射空间中寻找最优映射。FFM通过剪枝被证明永远不会成为最优映射组成部分的映射子集（即部分映射）来缩小搜索空间，从而快速消除所有包含这些部分映射的次优映射。随后FFM将部分映射拼接构建最优融合映射。使用FFM，我们相比采用手工优化融合的先进加速器TransFusion实现了最高1.8倍的能耗延迟积（EDP）降低。此外，我们证明FFM比现有自动映射器TileFlow和SET快数个数量级（>10,000倍）找到映射，且在相同运行时间内将EDP降低超过2倍。