Spatial dataflow accelerators are a promising direction for next-generation computer systems because they can reduce the memory bottlenecks of traditional von Neumann machines such as CPUs and GPUs. They organize computation around explicit, compiler-managed data movement over on-chip networks, allowing operands to be forwarded directly between processing elements and reducing reliance on high-latency, bandwidth-limited global shared memory. However, their performance depends strongly on how workloads are mapped to hardware. Naive mappings can perform poorly, and most users rely on hand-tuned vendor libraries. Thus, despite their potential for high performance, energy efficiency, and cost efficiency, limited programmability remains a major barrier to wider adoption. This paper presents TileLoom, an MLIR-based end-to-end framework that compiles tile-based programs, such as Triton kernels, onto spatial dataflow architectures. Unlike compiler frameworks that focus on optimizing code generation within a single tile, TileLoom distributes tile instances across spatially distributed cores and exploits the on-chip network and distributed memories to increase data reuse and reduce communication. TileLoom introduces a hardware representation that captures interconnect topology, memory hierarchy, and compute capabilities, enabling both architecture-specific optimizations and support for diverse spatial dataflow targets. In experiments on two generations of Tenstorrent systems, TileLoom achieves performance comparable to vendor libraries on various kernels.

翻译：空间数据流加速器因能缓解CPU和GPU等传统冯·诺依曼架构的内存瓶颈，成为下一代计算机系统的有前途方向。这类加速器通过显式的、编译器管理的片上网络数据移动来组织计算，使操作数可直接在处理单元间转发，从而减少对高延迟、带宽受限的全局共享内存的依赖。然而，其性能高度依赖于工作负载到硬件的映射方式。朴素映射方案可能表现不佳，多数用户依赖手工调优的厂商库。因此，尽管空间数据流加速器在性能、能效和成本效率方面潜力巨大，但有限的可编程性仍是其广泛应用的主要障碍。本文提出TileLoom——一个基于MLIR的端到端框架，可将Triton内核等基于瓦片的程序编译到空间数据流架构上。与专注于单个瓦片内代码生成优化的编译器框架不同，TileLoom将瓦片实例分布到空间分布的核上，并利用片上网络和分布式存储器来增加数据重用、减少通信开销。TileLoom引入了一种硬件表示方法，可捕获互连拓扑、存储层次和计算能力，从而既支持架构特定优化，又支持多样化的空间数据流目标。在两种Tenstorrent系统上的实验表明，TileLoom在各种内核上实现了与厂商库相当的性能。