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AMD, isn’t it your turn to show us something now... right?

Haebom
How can AMD compete effectively against Nvidia's CUDA technology? In the AI industry, using Nvidia's chipsets has pretty much become the only viable option. Google tried to push its TPU and others, but Nvidia has long since overtaken them in terms of performance. Actually, I’ve been recommending buying Nvidia since the start of this year.
Recently, I had some unused Radeon graphics cards lying around, so I tried testing AMD's ROCm. Honestly, compared to CUDA, it was a real hassle and I couldn't find any advantages. I also just wanted to make use of the Radeon I bought as an eGPU for my Mac a while back... But I couldn’t imagine Lisa Su just letting this slide, so I did a bit of research.
Nvidia has built a software ‘wall’ around its GPUs with CUDA, making it tough for other hardware companies to break into the HPC (High-Performance Computing) and AGI (General Artificial Intelligence) markets. But AMD is looking to overcome this with its HIP CUDA conversion tool and PyTorch. Also, AMD plans to challenge Nvidia's Grace-Hopper superchip with its soon-to-be-released Instinct MI300A processor.
Honestly, if you look at how things are now, Nvidia’s got a landslide victory going on. But as always, it’s pretty much impossible to have a total monopoly on technology—alternatives always show up, so I’m hopeful that AMD will make a breakthrough. Especially with the current shortage of AI chipsets, that’s even more likely.

Key Points and Insights

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The Role of PyTorch
PyTorch works without depending on CUDA, giving hardware vendors like AMD a way to get past the CUDA wall.
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Instinct MI300A Processor
AMD's Instinct MI300A processor is set to launch soon, and it's expected to be a strong competitor to Nvidia's Grace-Hopper superchip.
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Importance of the GenAI Market
The GenAI market keeps growing, and with that, GPU demand is rising as well. It looks like AMD could be competitive in this space.
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