Aussie AI

Full Text Online: Generative AI in C++

  • a new book by David Spuler, Ph.D.

Generative AI in C++: Coding Transformers and LLMs

Foreword

Preface

Source Code Availability

About the Author

About the Contributors

Part I: AI Projects in C++

Chapter 1. Introduction to AI in C++

Chapter 2. Transformers & LLMs

Chapter 3. AI Phones

Chapter 4. AI on Your Desktop

Chapter 5. Design Choices & Architectures

Chapter 6. Training, Fine-Tuning & RAG

Chapter 7. Deployment Architecture

Part II: Basic C++ Optimizations

Chapter 8. Bitwise Operations

Chapter 9. Floating Point Arithmetic

Chapter 10. Arithmetic Optimizations

Chapter 11. Compile-Time Optimizations

Chapter 12. Pointer Arithmetic

Chapter 13. Algorithm Speedups

Chapter 14. Memory Optimizations

Part III: Parallel C++ Optimizations

Chapter 15. Loop Vectorization

Chapter 16. Hardware Acceleration

Chapter 17. AVX Intrinsics

Chapter 18. Parallel Data Structures

Part IV: Transformer Components in C++

Chapter 19. Encoders & Decoders

Chapter 20. Attention

Chapter 21. Activation Functions

Chapter 22. Vector Algorithms

Chapter 23. Tensors

Chapter 24. Normalization

Chapter 25. Softmax

Chapter 26. Decoding Algorithms

Chapter 27. Tokenizer and Vocabulary

Part V: Optimizing Transformers in C++

Chapter 28. Deslugging AI Engines

Chapter 29. Caching Optimizations

Chapter 30. Vectorization

Chapter 31. Kernel Fusion

Chapter 32. Quantization

Chapter 33. Pruning

Chapter 34. MatMul/GEMM

Chapter 35. Lookup Tables & Precomputation

Chapter 36. AI Memory Optimizations

Part VI: Enterprise AI in C++

Chapter 37. Tuning, Profiling & Benchmarking

Chapter 38. Platform Portability

Chapter 39. Quality

Chapter 40. Reliability

Chapter 41. Self-Testing Code

Chapter 42. Debugging

Part VII: Research on AI Optimization

Chapter 43. Overview of AI Research

Chapter 44. Advanced Quantization

Chapter 45. Knowledge Distillation

Chapter 46. Structured Pruning

Chapter 47. Early Exit and Layer Pruning

Chapter 48. Width Pruning

Chapter 49. Length Pruning

Chapter 50. Adaptive Inference

Chapter 51. Zero-Multiplication Models

Chapter 52. Logarithmic Models

Chapter 53. Arithmetic Optimization Research

Chapter 54. Ensemble Multi-Model Architectures

Chapter 55. Advanced Number Systems

Chapter 56. Neural Architecture Search

Appendices

Appendix 1: C++ Slug Catalog

Bonus Appendix: C++ Bug Catalog

Bonus Appendix: C++ Bug Symptom Diagnosis

Bonus Appendix: C++ Portability Bug Catalog

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Generative AI in C++ The new Generative AI programming book by Aussie AI co-founders:
  • Generative AI coding in C++
  • Transformer engine speedups
  • LLM models
  • Phone and desktop AI
  • Code examples
  • Research citations

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Bonus Materials

Extra bonus materials for owners of the book.

References

Detailed reference lists for every chapter of the book.

Source Code

Access the source code for the Aussie AI C++ library as used in the book's examples..