From the course: NVIDIA Certified Associate AI Infrastructure and Operations (NCA-AIIO) Cert Prep
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CPU vs. GPU: Architectural difference - NVIDIA Tutorial
From the course: NVIDIA Certified Associate AI Infrastructure and Operations (NCA-AIIO) Cert Prep
CPU vs. GPU: Architectural difference
Let me give you a brief idea about high-level architecture of CPUs versus GPU. I'm not sure how many of you have this understanding, so I'm going to give you a very basic information about different architectural component of a CPU. So inside a CPU, there would be cores, like here it is a core, here it is a core, here it is a core, here it is a core. So this is your quad-core CPU, there are four cores. And then there are cache. Here it is L1 cache, level 1 cache. Then there could be L2 cache. And there can be L3 cache. This is a common architecture for modern CPUs where they have multiple cores. And they have their ALU, as we call it, arithmetic logical unit or control unit, as you can refer to them. And that allows you to perform control mechanism. And all of them may have their own individual cache, some common caches and maybe another larger L3 cache, level 3 cache. This is how a CPU architecture looks like. So like if I'm talking about Intel i9, i9 has 24 cores in it, right. Now…
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Inside an AI-centric data center4m 4s
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Power usage effectiveness (PUE)5m 4s
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The compute power4m 24s
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CPU and GPU7m 11s
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CPU vs. GPU: Architectural difference2m 48s
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Beyond Moore's Law2m 35s
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Data processing unit (DPU)6m 44s
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Network inside an AI-centric data center4m 50s
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Network fabric4m 43s
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Ethernet vs. InfiniBand7m 5s
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Converged Ethernet (CE)2m 31s
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Storage inside an AI-centric data center4m 21s
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Cloud vs. on-prem4m 11s
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