FlowTT: Exploiting Computation Flow Reuse in Irregular Tensor-Train Embedding
Results show that exposing prefix-shared computation is key to efficient TT-based embedding execution, and FlowTT, a flow-aware GPU execution framework that reformulates TT gather as a set of prefix-shared irregular computation flows, consistently achieves the lowest latency compared to existing methods.