README

modal.com · 2026-09-27 · by Long Nguyen ·generic

README

GPU Glossary GPU Glossary

GPU Glossary

Terminal Light green Light

Deploy on GPUs

TABLE OF CONTENTS

Home \-

README

Device Hardware \-

CUDA (Device Architecture)

Streaming Multiprocessor SM

Core

Special Function Unit SFU

Load/Store Unit LSU

Warp Scheduler

CUDA Core

Tensor Core

Tensor Memory Accelerator TMA

Streaming Multiprocessor Architecture

Texture Processing Cluster TPC

Graphics/GPU Processing Cluster GPC

Register File

L1 Data Cache

Tensor Memory

GPU RAM

Device Software \-

CUDA (Programming Model)

Streaming ASSembler SASS

Parallel Thread eXecution PTX

Compute Capability

Thread

Warp

Warpgroup

Cooperative Thread Array

Kernel

Thread Block

Thread Block Grid

Thread Hierarchy

Memory Hierarchy

Registers

Shared Memory

Global Memory

CUDA Tile Programming Model

Host Software \-

CUDA (Software Platform)

CUDA C++ (programming language)

NVIDIA GPU Drivers

nvidia.ko

CUDA Driver API

libcuda.so

NVIDIA Management Library NVML

libnvml.so

nvidia-smi

CUDA Runtime API

libcudart.so

CUDA Graphs

NVIDIA CUDA Compiler Driver nvcc

NVIDIA Runtime Compiler

NVIDIA CUDA Profiling Tools Interface CUPTI

NVIDIA Nsight Systems

CUDA Binary Utilities

cuBLAS

cuDNN

CUTLASS

CuTe

CuTe DSL

Performance \-

Performance Bottleneck

Roofline Model

Compute-bound

Memory-bound

Arithmetic Intensity

Overhead

Little's Law

Memory Bandwidth

Arithmetic Bandwidth

Latency Hiding

Warp Execution State

Active Cycle

Occupancy

Pipe Utilization

Peak Rate

Issue Efficiency

Streaming Multiprocessor Utilization

Warp Divergence

Scoreboard Stall

Branch Efficiency

Memory Coalescing

Bank Conflict

Register Pressure

Contributors

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README

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So we've read the PDFs from NVIDIA , lurked in the good Discords , and even bought dead-tree textbooks to put together a glossary that spans the whole stack in one place.

This glossary, unlike a PDF or a Discord or a book, is a hypertext document \-- all pages are inter-linked with one another, so you can jump down to read about the Warp Scheduler so you can better understand the threads that you came across in the article on the CUDA programming model .

You can also read it linearly. To navigate between pages, use the arrow keys, the arrows at the bottom of each page, or the table of contents (in the sidebar on desktop or in the hamburger menu on mobile).

The source for the glossary is available on GitHub .

Building on GPUs? We know a thing or two about it. Modal is an ergonomic Python SDK wrapped around a global GPU fleet. Deploy serverless AI workloads instantly without worrying about quota requests, driver compatibility issues, or managing bulky ML dependencies. Deploy serverless AI workloads instantly without worrying about quota requests, driver compatibility issues, or managing bulky ML dependencies. Deploy on GPUs

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