← Wednesday, October 7, 2026Performance & OSDeep dive
FBTriton embedding kernels outperform legacy CUDA on sharded GPU workloads
The post describes Triton forward and backward kernels for table-batched embeddings, including a generic gather and a small-table histogram fast path; it reports outperforming legacy CUDA kernels. Kernel design for workloads spanning thousands of sharded GPUs is relevant to performance engineering.
- What
- FBTriton implements Table-Batched Embedding forward and backward kernels for embedding lookups across sharded GPUs.
- How
- The forward pass gathers rows, optionally weights them, and pools them; a specialized small-table path uses a histogram and tensor-core operations.
- Why it matters
- Reusing forward histogram counts cut combined latency by 16.8% on a large B200 configuration, while keeping forward and backward as separate launches.
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