No, still not clear — you can access the memory of all of them, but nobody has yet confirmed you can launch kernels on remote GPUs.
AI HARDWARE
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Distributed Training Necessity for Model Sizes
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same – for models of that size, not sure why you actually need distributed training either.
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LLM Requires 12GB VRAM: GPU Memory Breakdown Analysis
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8 GB of video RAM for LLM, then 2 GB for ASR, and 2 GB for the game. Total requirement is 12 GB. I know it's quite high but we need to start somewhere.
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India launches Airawat AI supercomputer for advanced computing
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For more information, tap here: https://
airawat.cdac.in @GoI_MeitY @abhish18 @_DigitalIndia #PowerofAirawat #AISupercomputing #IndiaAI #DigitalIndia #FutureOfAI #AIForGood #InnovationImpact #IndiaTechPride #gpu #supercomputing -
India Launches AIRAWAT: AI and Supercomputing Initiative
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The future is here, and it’s powered by AIRAWAT! Join us in celebrating India’s leap into AI and supercomputing. The journey has just begun! For more information, tap here: https://
airawat.cdac.in -
GPU Resource Allocation: Balancing Optimization with Debugging Flexibility
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A fully optimized system might wind up with persistent kernels running continuously on all GPUs, but I want the ability to debug a single process using all GPUs, as well as launch parallel experiments directly from one host without needing a cluster layer.
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Grace GPU cluster kernel launch and multi-GPU operation capabilities
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Can you comment on my original question — can a process on one grace CPU launch kernels and operate on all 72 GPUs, or do you need to treat it as 18 separate hosts that just happen to have great NCCL connectivity?
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AIRAWAT Accelerates AI Research in NLP and Computer Vision
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AIRAWAT significantly accelerates AI research in areas like NLP, computer vision, and more, enabling faster training times and empowering researchers to tackle more complex computational challenges than ever before. Imagine the potential it brings to India’s AI-driven future.
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AIRAWAT: India’s High-Performance AI Computing Infrastructure Launch
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Learn more: https://
airawat.cdac.in @GoI_MeitY @abhish18 @_DigitalIndia #SpeedOfInnovation #TechStats #PowerofAirawat -
Hardware and Software Must Co-Develop for AI Chips
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HW or SW in #AI chip development? At @ventureLABca
's #HardTechSummit, UAI's Alex Grbic emphasized the symbiotic reality: 'You can't build a high-performance chip, then add software support after. They have to work together." See more in @CMO_Daily
's recap.