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Browse subtopics: AI Compute

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Cloud TPU

Cloud TPU is Google Cloud's offering of Tensor Processing Units (TPUs), the family of custom application-specific integrated circuits (ASICs) that Google builds to accelerate machine learning training and…

AI ComputeAI Hardware

FLOPS

FLOPS (floating-point operations per second, also written FLOP/s) is a measure of computing speed: the number of arithmetic operations on floating-point numbers that a processor, accelerator or supercomputer…

AI ComputeAI Hardware

GPU computing

GPU computing is the use of a graphics processing unit (GPU) to perform general-purpose computation that was traditionally handled by the central processing unit (CPU).

AI ComputeAI Hardware

MLPerf

MLPerf is the AI industry's standard suite of benchmarks for measuring how fast machine learning systems train and run models, developed and maintained by MLCommons

AI BenchmarksAI Compute

Microscaling formats

Microscaling (MX) formats are a family of low-precision number formats for machine learning in which a small block of values, normally 32 of them, shares one common scale factor while each value is stored in a…

AI ComputeAI Hardware

NVFP4

NVFP4 (NVIDIA FP4) is a 4-bit floating-point number format introduced by Nvidia with the Blackwell GPU architecture.

AI ComputeAI Hardware

TPU Pod

A TPU Pod is a single Google supercomputer built from many Tensor Processing Unit (TPU) chips wired directly to each other by a high-speed Inter-Chip Interconnect (ICI) fabric arranged as a 2D or 3D torus, so…

AI ComputeAI Hardware

Training compute

Training compute is the total number of floating-point operations (FLOP) performed to train a machine learning model, normally counted over the forward and backward passes of the final training run.

AI ComputeTraining & Optimization