MLOps & Infrastructure · beginner · concept 193 of 311 · Updated Nov 4, 2026
GPU & TPU Computing
GPUs (NVIDIA) and TPUs (Google) are the hardware that makes deep learning possible. Their parallel processing capabilities accelerate matrix operations by 100x+ versus CPUs. This is the same lineage as high-performance computing: AI clusters are supercomputers, ranked and benchmarked as such.
Top AI contributors on this
- Jensen HuangNvidia
- Jeff DeanDiscovery Loop
- Clément DelangueHugging Face
- Satya NadellaMicrosoft
- Sundar PichaiAlphabet / Google
- Alexandr WangMeta
Key terms
CUDATensor coresHBMAccelerator generations (Hopper, Blackwell, Rubin)TPUParallelismHPC & supercomputing
Videos
▶ GPUs: Explained ↗
IBM Technology · YouTube
Guides and articles
Which GPU for deep learning? ↗
Tim Dettmers
The Hardware Lottery ↗
Sara Hooker
Courses, papers, and more
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