Koduri: AI chip design focus shifts to memory
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SK hynix published the 4th article in its AI ecosystem series, written by OXMIQ Labs founder and CEO Raja Koduri, explaining that the focus of AI semiconductor design is shifting toward memory. The article notes that compute units consume only a few femtojoules, while fetching data from off-chip DRAM can cost hundreds or even thousands of times more energy; meanwhile, Transformer models have massive parameters with little data reuse, invalidating the cache assumptions of traditional architectures. Based on these factors, the performance bottleneck of AI systems is shifting from compute to data delivery, and memory is becoming the starting point of architectural design. The article series is still being updated, and there are no other new developments at this time.
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- SK hynix Memory Technology[AI Ecosystem] The semiconductor paradigm shifts toward memory
Part 4 of SK hynix's AI ecosystem series has been published, in which OXMIQ Labs founder and CEO Raja Koduri explains how the focus of AI semiconductor design is shifting toward memory. The article notes that compute units consume only a few femtojoules, while fetching data from off-chip DRAM can cost hundreds or even thousands of times more; Transformer models have huge parameters and little data reuse, invalidating cache assumptions. The performance bottleneck of AI systems is shifting from compute to data supply, making memory the starting point of architecture design.
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