Google launches 'TorchTPU' initiative to enhance TPU compatibility with PyTorch, aiming to rival Nvidia's GPU market lead ...

Alphabet's Google is working on a new initiative to make its artificial intelligence chips better at running PyTorch, the ...

Google develops TorchTPU to make PyTorch run more smoothly on TPUs, aiming to challenge Nvidia, broaden cloud AI workloads, ...

The new initiative, known internally as “TorchTPU,” aims to remove a key barrier that has slowed adoption of TPU chips by ma ...

Google (GOOG) (GOOGL) is working to lessen Nvidia's (NVDA) advantage with its CUDA software platform, with some help from ...

TPUv7 offers a viable alternative to the GPU-centric AI stack has already arrived — one with real implications for the economics and architecture of frontier-scale training.

GPUs, born to push pixels, evolved into the engine of the deep learning revolution and now sit at the center of the AI ...

Google’s TPUs cannot dethrone Nvidia’s GPUs. But, there is a bigger challenge that can seriously threaten Nvidia’s growth trajectory.

Apple Starflow is open source and requires Python, PyTorch, and a GPU, so you can try research builds and measure speed gains ...

Software compatibility differs substantially, with Nvidia supporting CUDA, TensorRT-LLM, PyTorch, JAX and Triton, while Google’s TPU works with JAX/XLA, TensorFlow and emerging PyTorch/XLA, according ...

Google’s new TPU generations, including Trillium and Ironwood, are emerging as the strongest challenge yet to Nvidia’s GPU ...

Enabling Dataflow Execution on GPUs with Spatial Pipelines” was published by researchers at NVIDIA and the University of ...