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Nvidia Part III: The Dawn of the AI Era (2022-2023)
Acquired
Cores, parallel, on chip memory
The bottleneck in computer performance is exacerbated by the increasing speed of CPUs and memory size due to limited architecture, particularly through a single channel known as a bus. To overcome this limitation, a shift from von Neumann architecture to parallel processing and incorporating more processors or cores is essential. NVIDIA's hardware advancements and AI researchers have optimized software to enable parallel execution. However, the current constraint for massive language models is not the clock speed or number of cores, but the amount of on-chip memory. This shift underscores the significance of the work done by NVIDIA and in data centers.
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