![]() ![]() That’s not possible given that the largest models measure in the billions or trillions of parameters.Ī popular solution is to use high bandwidth memory (HBM), which involves connecting a 3D stack of 4, 8 or 12 DRAM die to the processor via a silicon interposer. ![]() ![]() In an ideal world, an entire model could be stored in a processor, an approach that would eliminate off-chip memory from the equation. Where yesterday’s systems were memory-constrained, today’s data center architectures use a variety of techniques to overcome memory bottlenecks.Īmong the criticisms aimed by skeptics at current AI technology is that the memory bottleneck – caused by inability to accelerated the data movement between processor and memory – is holding back useful real-world applications.ĪI accelerators used to train AI models in data centers require the highest memory bandwidth available. ![]()
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