EdgeKernelBench: Unified LLM-Driven Kernel Generation for Edge Backends
We introduce EdgeKernelBench, which combines a unified IR deployment framework with a hierarchical benchmark for edge workloads.
ProofPaper ↗
Key points
- Recent works show that LLMs can generate kernels with strong performance on server GPUs.
- LLM kernel generation across diverse edge backends has yet to be studied systematically.
- We therefore introduce the Layered Edge Kernel Agent (LEKA), which organizes optimization through a layered IR.
- Together, EdgeKernelBench and LEKA support unified evaluation and layered optimization of kernels generated by LLMs across edge backends.
Sources (2)
- [1]EdgeKernelBench: Unified LLM-Driven Kernel Generation for Edge BackendsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 17, 11:51 AM
We introduce EdgeKernelBench, which combines a unified IR deployment framework with a hierarchical benchmark for edge workloads.
Recent works show that LLMs can generate kernels with strong performance on server GPUs.
- [2]EdgeKernelBench: Unified LLM-Driven Kernel Generation for Edge BackendsHugging Face Daily Papers · Oct 17, 12:00 AM · same content
Extractive summary: sentences quoted from the sources.
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