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🔧 ProgrammierungGetting started with JAX on NVIDIA GPUs(26.08.2026 um 21:03 Uhr)
🔧 ProgrammierungScale JAX models to multi-GPU systems(26.08.2026 um 21:03 Uhr)
🔧 ProgrammierungHow to build and scale multi-agent AI systems on GKE(27.08.2026 um 00:42 Uhr)
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🎥 PodcastsThe AI skill everyone should have(24.08.2026 um 22:00 Uhr)
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26 🕛 kürzlich 1 Min Lesezeit 7 Leser online ️ CVE-RADAR
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Getting started with JAX on NVIDIA GPUs

↗ Quelle (YouTube · Google Cloud Tech)
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YouTube · Google Cloud Tech
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Join the Google Cloud & NVIDIA community → https://g.dev/cloud/google-nvidia-community

Master the fundamentals of JAX on NVIDIA GPUs and learn how to configure a Google Kubernetes Engine (GKE) cluster for high performance GPU-accelerated computing. Join Ivan Nardini, AI Engineer at Google Cloud and Ekaterina Sirazitdinova, Developer Advocate at NVIDIA teach:
* *How to verify an NVIDIA GPU* visibility instantly using nvidia\-smi and JAX device diagnostics.
* *Discuss how the XLA compiler* traces and compiles Python code into optimized machine instructions.
* *How to eliminate performance bottlenecks* caused by host-to-device data transfers and asynchronous dispatch latency.

This is part 1 of JAX on NVIDIA GPUs Crash Course.

Watch more JAX on NVIDIA GPUs Crash Course → https://g.dev/cloud/jax-nvidia-gpu
🔔 Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech

Speakers: Ivan Nardini, Ekaterina Sirazitdinova
Products Mentioned: Google Cloud, JAX
Vollständiger Original-Bericht
Ausführliche Details, Code-Beispiele & Hersteller-Stellungnahme auf youtube.com.
↗ Original-Artikel auf youtube.com lesen
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