Understanding LLM Model Sizes and Hardware Requirements
Chapter 1: Introduction to Large Language Models and Size
What is a Large Language Model (LLM)?
Understanding Model Parameters
How Model Size is Measured
Examples of Different Model Sizes
Quiz for Chapter 1
Chapter 2: Essential Hardware Components for AI
The Central Processing Unit (CPU)
Random Access Memory (RAM)
The Graphics Processing Unit (GPU)
Video RAM (VRAM)
Brief Overview of TPUs
Quiz for Chapter 2
Chapter 3: Connecting Model Size to Hardware Needs
Model Parameters and Memory Consumption
Data Types and Precision (FP16, INT8)
Introduction to Quantization
Compute Requirements (FLOPS)
Memory Bandwidth Importance
Quiz for Chapter 3
Chapter 4: Running LLMs: Inference vs. Training
What is Model Inference?
Hardware Needs for Inference
What is Model Training?
Hardware Needs for Training
Focus on Inference Requirements
Quiz for Chapter 4
Chapter 5: Estimating Hardware Needs
Rule of Thumb: Parameters to VRAM
Accounting for Activation Memory
Factors Influencing Actual Usage
Checking Hardware Specifications
Practice: Simple VRAM Estimations
Quiz for Chapter 5
Rule of Thumb: Parameters to VRAM
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- Automatic Mixed Precision for Deep Learning, NVIDIA Developer Documentation, 2023 (NVIDIA) - Explains the principles and benefits of using mixed precision (FP16 and FP32) in deep learning, crucial for understanding memory and performance optimizations on GPUs.
- Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference, Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Andrey Bochenin, Vitaly Tarasov, Andrew Karpov, Dianne Jouppi, Anujan Varma, Gabriel Micha, 2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (IEEE) DOI: 10.1109/CVPR.2018.00696 - A foundational academic paper introducing techniques for quantizing neural networks to 8-bit integers (INT8) for efficient inference, directly relevant to memory reduction.
- VRAM estimation for large models, Hugging Face documentation contributors, 2023 (Hugging Face) - A practical guide from a leading LLM platform detailing how to estimate VRAM requirements for large language models, including considerations for different data types and additional memory overheads.