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

2024·4.4 MB·English
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by David Spuler| 2024| 4.4| English

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

Do you know C++ but not AI? Do you dream of writing your own Generative AI engine in C++? From beginner to advanced, this book covers the internals of GPT-style Transformer engines and Large Language Models (LLMs) in C++, with source code examples and research paper citations.Key FeaturesTransformer components in C++Faster and smarter AIOpen source LLMsAdvanced software developmentCutting-edge research optimizationsJust C++ code without all the mathResearch papers literature surveyTable of ContentsPart AI Projects in C++1. Introduction to AI in C++2. Transformers and u0026 LLMs3. AI Phones4. AI on Your Desktop5. Design Choices and u0026 Architectures6. Training, Fine-Tuning and u0026 RAG7. Deployment ArchitecturePart II: Basic C++ Optimizations8. Bitwise Operations9. Floating Point Arithmetic10. Arithmetic Optimizations11. Compile-Time Optimizations12. Pointer Arithmetic13. Algorithm Speedups14. Memory OptimizationsPart III: Parallel C++ Optimizations15. Loop Vectorization16. Hardware Acceleration17. AVX Intrinsics18. Parallel Data StructuresPart IV: Transformer Components in C++19. Encoders and u0026 Decoders20. Attention21. Activation Functions22. Vector Algorithms23. Tensors24. Normalization25. Softmax26. Decoding Algorithms27. Tokenizer and VocabularyPart V: Optimizing Transformers in C++28. Deslugging AI Engines29. Caching Optimizations30. Vectorization31. Kernel Fusion32. Quantization33. Pruning34. MatMul GEMM35. Lookup Tables and u0026 Precomputation36. AI Memory OptimizationsPart VI: Enterprise AI in C++37. Tuning, Profiling and u0026 Benchmarking38. Platform Portability39. Quality40. Reliability41. Self-Testing Code42. DebuggingPart VII: Research on AI Optimization43. Overview of AI Research44. Advanced Quantization45. Knowledge Distillation46. Structured Pruning47. Early Exit and Layer Pruning48. Width Pruning49. Length Pruning50. Adaptive Inference51. Zero-Multiplication Models52. Logarithmic Models53. Arithmetic Optimization Research54. Ensemble Multi-Model Architectures55. Advanced Number Systems56. Neural Architecture SearchAppendix 1: C++ Slug Catalog

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Author:David Spuler
Publication Year:2024
Language:English
File Size:4.4
Format:PDF
Price:FREE
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