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rerx | 2 years ago
> Even Nvidia itself has tools that do not exclusively rely on CUDA. For example, Triton Inference Server is an open-source tool by Nvidia that simplifies deploying AI models at scale, supporting frameworks like TensorFlow, PyTorch, and ONNX. Triton also provides features like model versioning, multi-model serving, and concurrent model execution to optimize the utilization of GPU and CPU resources.
> Nvidia's TensorRT is a high-performance deep learning inference optimizer and runtime library that accelerates deep learning inference on Nvidia GPUs. [...]
Keller was speaking of OpenAI's Triton (https://openai.com/research/triton), a Python-like language that is compiled to code for Nvidia GPUs, but Tom's Hardware mixed this up with Nvidia's Triton Inference Server, a higher level tool that's really not a replacement for CUDA and not directly related to the Triton language. Easy to confuse these if you are a writer in a hurry.
p1esk|2 years ago
diggan|2 years ago
> His statements also imply that even though he has worked stints at some of the largest chipmakers in the world, including the likes of Apple, Intel, AMD, Broadcom (and now Tenstorrent), we might not see his name on the Nvidia roster any time soon.
shash|2 years ago
londons_explore|2 years ago
chrisjc|2 years ago
Wasn't this one of the reasons AMD abandoned/deprioritized their efforts on such a project?
95014_refugee|2 years ago