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AMD, it's about time you showed something... right?
Haebom
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How can AMD compete with Nvidia's CUDA technology? In the AI industry, using Nvidia's chipsets is now the only option. Although Google's TPU and others were there, Nvidia's chipsets have already surpassed them in terms of performance. In fact, I have been maintaining my Nvidia buy recommendation since the beginning of this year.
Recently, I tested AMD ROCm because I had some Radeon graphics cards that I personally didn't use, but to be honest, it was very cumbersome compared to CUDA, and I couldn't find any advantages at all. I also tried it because I felt bad about wasting the Radeon that I bought as an eGPU for my Mac a while ago... I didn't think our Lisa Su would be treated like this, so I looked into it.
Nvidia has built a software “wall” around its GPUs with CUDA, making it difficult for other hardware companies to enter the HPC (High-Performance Computing) and AGI (General Artificial Intelligence) markets. However, AMD is trying to solve this problem with its HIP CUDA conversion tool and PyTorch. AMD also plans to provide competition to Nvidia’s Grace-Hopper superchip with its upcoming Instinct MI300A processor.
Honestly, looking at the current behavior, Nvidia is winning by a landslide. However, as always, it is almost impossible to monopolize technology, and substitutes are bound to appear, so I expect AMD to advance. This is especially true considering the current shortage of AI chipsets.
Key Points and Insights
The Role of PyTorch
PyTorch can work without relying on CUDA, providing a way for other hardware vendors like AMD to get around the CUDA wall.
Instinct MI300A Processor
AMD's Instinct MI300A processor is due out soon and is expected to compete with Nvidia's Grace-Hopper superchip.
Importance of GenAI Market
The GenAI market continues to grow, and with it, the demand for GPUs. AMD appears to be able to compete in this market.
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