Generative AI in C++: Coding Transformers and LLMs (Generative AI LLM Programming)

Spuler, David

/ ISBN 13: 9798871928684

Verlag: Independently published, 2024

Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind. Bestandsnummer des Verkäufers rev2978153445

Inhaltsangabe:

Do you know C++ but not AI? Do you dream of writing your own AI engine in C++? From beginner to advanced, this book covers the internals of AI engines in C++, with real source code examples and research paper citations.

Key Features

• Transformer components in C++
• Faster and smarter AI
• Play with an AI engine on your desktop
• Cutting-edge research optimizations
• Just C++ code without all the math

Table of Contents

Part I: AI Projects in C++
1. Introduction to AI in C++
2. Transformers & LLMs
3. AI Phones
4. AI on Your Desktop
5. Design Choices & Architectures
6. Training, Fine-Tuning & RAG
7. Deployment Architecture

Part II: Basic C++ Optimizations
8. Bitwise Operations
9. Floating Point Arithmetic
10. Arithmetic Optimizations
11. Compile-Time Optimizations
12. Pointer Arithmetic
13. Algorithm Speedups
14. Memory Optimizations

Part III: Parallel C++ Optimizations
15. Loop Vectorization
16. Hardware Acceleration
17. AVX Intrinsics
18. Parallel Data Structures

Part IV: Transformer Components in C++
19. Encoders & Decoders
20. Attention
21. Activation Functions
22. Vector Algorithms
23. Tensors
24. Normalization
25. Softmax
26. Decoding Algorithms
27. Tokenizer and Vocabulary

Part V: Optimizing Transformers in C++
28. Deslugging AI Engines
29. Caching Optimizations
30. Vectorization
31. Kernel Fusion
32. Quantization
33. Pruning
34. MatMul/GEMM
35. Lookup Tables & Precomputation
36. AI Memory Optimizations

Part VI: Enterprise AI in C++
37. Tuning, Profiling & Benchmarking
38. Platform Portability
39. Quality
40. Reliability
41. Self-Testing Code
42. Debugging

Part VII: Research on AI Optimization
43. Overview of AI Research
44. Advanced Quantization
45. Knowledge Distillation
46. Structured Pruning
47. Early Exit and Layer Pruning
48. Width Pruning
49. Length Pruning
50. Adaptive Inference
51. Zero-Multiplication Models
52. Logarithmic Models
53. Arithmetic Optimization Research
54. Ensemble Multi-Model Architectures
55. Advanced Number Systems
56. Neural Architecture Search
Appendix 1: C++ Slug Catalog

Bibliografische Details

Titel: Generative AI in C++: Coding Transformers ...
Verlag: Independently published
Erscheinungsdatum: 2024
Einband: Softcover
Zustand: Like New