causal-conv1d

Headlines · 2

1. 2d
   Developer Ports PyTorch 2.7.1 and Mamba-1 to Legacy NVIDIA GPUs

   A developer announced a Windows port of an LLM training stack for NVIDIA GPUs from SM 3.5 through SM 7.5, including a custom PyTorch 2.7.1 build with CUDA 11.8, ported causal-conv1d, native-CUDA Mamba-1 and Windows NCCL. The author reports that Mamba-1 works across those architectures and achieved a maximum absolute error of 3.8e-06 against a PyTorch reference on a 2013 Tesla K40c. Mamba-2 and Mamba-3 require Turing or newer because they depend on Triton and TileLang, while older GPUs automatically fall back to Mamba-1.

   r/LocalLLaMA · 🔥 0
2. Oct 14
   Databricks cuts Qwen 27B fine-tuning time 6x on AI Runtime

   A Databricks blog details systematic performance work that cut supervised fine-tuning of Qwen 3.8 27B on AI Runtime from 7 hours 44 minutes to 1 hour 17 minutes on a fixed dataset, roughly a 6x speedup. The authors note that 98% GPU utilization only shows the GPU was busy, not how efficiently it was used, so they used torch traces to find where time was actually spent. Optimizations included enabling the flash-linear-attention and causal-conv1d fused kernels and reworking batch packing, which alone gave a 1.6x improvement from 2 hours 5 minutes to 1 hour 17 minutes. Example code is published in the AI Runtime cookbook.

   Databricks Blog · 🔥 0

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