CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits
AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchmarks, however, focus almost exclusively on CUDA and Triton, leaving hardware ecosystems with less-exposed programming models without a common evaluation baseline. We present CANN Bench, an open benchmark for AI-generated operator code on Huawei's Ascend NPU. The current release covers 53 operators and 1060 test cases organized into four difficulty tiers -- from simple elementwise primitives to MoE dispatch and FlashAttention kernels -- spanning FP16, BF16, FP32, and INT8 precision formats. Evaluation adopts a \textbf{three-dimensional weigh...
| Authors | Xue-Jian Gao, Deng Pan, Yueming Su et al. |
|---|---|
| Primary category | cs.AI |
| Published | 8 July 2026 |
| Last updated at source | 8 July 2026 |
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