Cleave: Scaling Tensor Program Optimization via Decoupled Algebraic Search and Operator Scheduling
Optimized kernels such as FlashAttention and FlashDecoding are crucial for accelerating today's large models. Most of them are handwritten by experts because existing ML compilers cannot match their efficiency. Producing such kernels requires fusing computations with multiple reductions, which requires both algebraic transformation of the computation graph and operator scheduling of the transformed graph. Unfortunately, searching the two jointly yields a space too large to navigate. We propose Cleave, an ML compiler built on symbolic decoupling: Cleave discovers transformations by performing superoptimization on a graph with symbolic shapes, and then schedules each resulting graph on conc...
| Authors | David Pissarra, Jinkun Lin, Haitian Jiang et al. |
|---|---|
| Primary category | cs.PL |
| Published | 6 October 2026 |
| Last updated at source | 6 October 2026 |
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