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

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

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Description: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 & LLMs3. AI Phones4. AI on Your Desktop5. Design Choices & Architectures6. Training, Fine-Tuning & 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 & 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 & Precomputation36. AI Memory OptimizationsPart VI: Enterprise AI in C++37. Tuning, Profiling & 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 CatalogWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Generative AI in C++: Coding Transformers and LLMs (Generative AI LLM Programming). To get started finding Generative AI in C++: Coding Transformers and LLMs (Generative AI LLM Programming), you are right to find our website which has a comprehensive collection of manuals listed.
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Description: 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 & LLMs3. AI Phones4. AI on Your Desktop5. Design Choices & Architectures6. Training, Fine-Tuning & 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 & 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 & Precomputation36. AI Memory OptimizationsPart VI: Enterprise AI in C++37. Tuning, Profiling & 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 CatalogWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Generative AI in C++: Coding Transformers and LLMs (Generative AI LLM Programming). To get started finding Generative AI in C++: Coding Transformers and LLMs (Generative AI LLM Programming), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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

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

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