Accelerate PyTorch workloads with Cloud TPUs and OpenXLA
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7 часов – 1 862 0129:26Опубликовано 16 мая 2024, 14:08
Google Cloud AI accelerators enable high-performance, cost-effective training and inference for leading AI/ML frameworks. In this session, get the latest news on PyTorch/XLA, developed collaboratively by Google, Meta, and partners in the AI ecosystem to utilize OpenXLA for accelerating PyTorch workloads.
Github → goo.gle/3xQeFaC
Cloud Tensor Processing Units (TPUs) → goo.gle/tpu
Speakers: Shauheen Zahirazami
Watch more:
Check out all the AI videos at Google I/O 2024 → goo.gle/io24-ai-yt
Check out all the Cloud videos at Google I/O 2024 → goo.gle/io24-cloud-yt
Check out all the Mobile videos at Google I/O 2024 → goo.gle/io24-mobile-yt
Check out all the Web videos at Google I/O 2024 → goo.gle/io24-web-yt
Subscribe to Google Developers → goo.gle/developers
#GoogleIO
Products Mentioned: Cloud - AI and Machine Learning - Cloud TPU
Event: Google I/O 2024
Github → goo.gle/3xQeFaC
Cloud Tensor Processing Units (TPUs) → goo.gle/tpu
Speakers: Shauheen Zahirazami
Watch more:
Check out all the AI videos at Google I/O 2024 → goo.gle/io24-ai-yt
Check out all the Cloud videos at Google I/O 2024 → goo.gle/io24-cloud-yt
Check out all the Mobile videos at Google I/O 2024 → goo.gle/io24-mobile-yt
Check out all the Web videos at Google I/O 2024 → goo.gle/io24-web-yt
Subscribe to Google Developers → goo.gle/developers
#GoogleIO
Products Mentioned: Cloud - AI and Machine Learning - Cloud TPU
Event: Google I/O 2024
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