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…As part of its latest announcements, Google announced a slew of upgrades to Hypercomputer which include new virtual machines powered by custom Arm-based CPUs, eight generation tensor processors, native PyTorch TPU…
…The transition proved effortless. “Our code was already in PyTorch, so translating everything to the AMD stack and ROCm software took one engineer roughly half a day,” says Azimian. The open-source…
…With CUDA optimizations, the Spark gets a 2x improvement in Omniverse Issac Sim, while other models such as Qwen3 30B, Stable Diffusion 3.5 see over 30% uplift, and PyTorch updates also…
…Furiosa’s SDK leverages a general compiler that automatically maps high-level PyTorch code to silicon. For developers requiring more granular control, Furiosa’s Virtual ISA offers a declarative programming model that…
Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate
Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate
Show HN: We built an LLM inference engine in pure Python – no PyTorch, no Triton
Hi HN,I'm Danilo. I've been struggling with the limitations of AdamW when fine-tuning LLMs locally. Second-order optimizers (like Shampoo or SOAP) offer significantly better step-convergence by exploiting Kronecker-facto…
I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work …
…The company also continues its support for PyTorch which now adds FP32 and FP16 mixed precision. This is great work by the AMD software team who are strengthening the ROCM 6.0…
…Do you have a public model I could look at? You're using the example image classification script in Transformers ( https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification ) or…
…Chat, etc; advanced LLM use-cases on PyTorch with ROCm; local LLM-assisted software development with VS Code and Qwen3-Coder-30B; and workflow automation with n8n and GPT-OSS-120B models…
…46.6% of correct kernels are slower than the PyTorch eager baseline, and cross-hardware speedup variance reaches 21.4times. Besides, quantization remains completely unsolved (0/30 successes) despite non-trivial compilation…
…Ising Decoding Leverage cuQuantum cuStabilizer and PyTorch to efficiently train state-of-the-art models for your specific QPU data, wherever you need. Get Started With NVIDIA Ising Start deploying AI models…
…ModelOpt accepts Hugging Face, PyTorch, or ONNX format models as input and provides Python APIs for users to easily combine different optimization techniques to produce optimized checkpoints. ModelOpt supports highly performant quantization…
