MLIR

Headlines · 2

1. Oct 20
   Google Research completes 32-bit Coral NPU, releases v1.0 compiler and Coralboards

   Google Research announced the completed 32-bit Coral NPU architecture, including a new Matrix Execution Unit it says is configurable up to 1 TOPS and targets 10mW average power for inference, plus Coral Compiler v1.0, an open-source IREE/MLIR-based stack that takes JAX, PyTorch and TensorFlow models to the Coral NPU target. The full 32-bit RTL, including the Milestone 4 matrix unit, is available on GitHub, and Google also unveiled second-generation Synaptics Astra SR200 microcontrollers rated at 400 GOPS, while Synaptics Coralboard SL (1 TOPS) and Coralboard SR kits are sold through DigiKey, which TechNews reported as exclusive global distributor. The performance and power figures remain vendor claims and were not independently benchmarked in the reports.

   Google Developers Blog · 🔥 0
2. Oct 19
   HardenedLinux releases SonicBoom v0.0.3, a compiler-first inference runtime

   The HardenedLinux community announced SonicBoom v0.0.3, an open-source GPLv3 inference runtime that it describes as compiler-first and free of Python at build or run time, using one shared library, a C ABI and Guile Scheme as its first-class language. On a single RTX 3050 8GB, the team self-reported that Gemma 4 E4B Q3_K_M reached 1.18× llama.cpp's decode speed and 1.00× prefill, while Qwen2.5-0.5B Q4_K_M reached 1.12× and 1.09×; Qwen decode at depth 512 was 0.98×. The team acknowledges it tested only one GPU and is asking NVIDIA owners to run a one-command benchmark and post results.

   r/LocalLLaMA · 🔥 0

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