Back to Basics: The Abstract Machine Bob Steagall CppCon 2020 K E W B C O M P U T I N GCopyright © 2020 Bob Steagall K E W B C O M P U T I N G Overview/Goals • Describe abstract machines in general general • Describe the C++ abstract machine specifically • Language goals that drive its design • Role in program development and execution • Important definitions and characteristics • Important components components of the abstract machine, and their relationships • Provide a useful overview of the C++ abstract machine CppCon 2020 - The Abstract Machine 2Copyright © 2020 Bob Steagall K E W B C O M P U T I

Leveraging the power of C++ for efficient machine learning on embedded devices Adrian Stanciu adrian.stanciu.pub@gmail.com CppCon, 2023 1 / 50About me ◮ I am a software engineer from Romania ◮ I have Motivation ◮ Image classification ◮ Hand gesture recognition ◮ Summary ◮ Q&A 4 / 50Motivation 5 / 50Machine Learning (ML) ◮ Subfield of Artificial Inteligence (AI) ◮ Enables computers to learn from data and consumption ◮ May have real-time performance constraints 7 / 50Machine learning on embedded devices ◮ Alternative to cloud-based machine learning ◮ Advantages: ◮ Real-time processing ◮ Low latency ◮

micrograd++: A 500 line C++ Machine Learning Library Gautam Sharma Independent Researcher gautamsharma2813@gmail.com Abstract—micrograd++ is a pure C++ machine learning li- brary inspired by Andrej Karpathy’s framework for building and training machine learning models. By leveraging the performance efficiency of C++, micro- grad++ offers a robust solution for integrating machine learning capabilities directly into Traditionally, all machine learning libraries are extremely bulky and very hard to integrate as third party dependencies. This aspect scares practitioners to adopt a C++ based machine learning library for

In this talk I'll tell you about C++ AoT compiler, JiTs for dynamic language, JiTs for binary translation, and dive back 20, 30, 40, 50, 60 years, way back into compiler history and read wonderful academic compile code to a target machine, then run it. X mapping never changes.? Interpreter Is an interpreter a JiT, or AoT? What if it modifies its bytecode? A CPU executes machine code… an interpreter executes executes bytecode… That’s the same thing, a CPU is an interpreter for machine code. A compiler can perform partial evaluation of a program, thereby interpreting it… The compiler itself can be compiled

. . . . . . . . . 18 1.8 Creating your first virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.9 Running your virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 1.9.5 Resizing the machine’s window . . . . . . . . . . . . . . . . . . . . . . 25 1.9.6 Saving the state of the machine . . . . . . . . . . . . . . . . . . . . . . 26 1.10 2 Snapshot contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1.12 Virtual machine configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 1.13 Removing virtual machines

. . . . . . . . . 18 1.8 Creating your first virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.9 Running your virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 1.9.5 Resizing the machine’s window . . . . . . . . . . . . . . . . . . . . . . 25 1.9.6 Saving the state of the machine . . . . . . . . . . . . . . . . . . . . . . 26 1.10 2 Snapshot contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1.12 Virtual machine configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 1.13 Removing virtual machines

. . . . . . . . . 17 1.7 Creating your first virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.8 Running your virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1.8.5 Resizing the machine’s window . . . . . . . . . . . . . . . . . . . . . . 24 1.8.6 Saving the state of the machine . . . . . . . . . . . . . . . . . . . . . . 25 1.9 2 Snapshot contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 1.11 Virtual machine configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1.12 Removing virtual machines

. . . . . . . . . 17 1.7 Creating your first virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.8 Running your virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1.8.5 Resizing the machine’s window . . . . . . . . . . . . . . . . . . . . . . 24 1.8.6 Saving the state of the machine . . . . . . . . . . . . . . . . . . . . . . 24 1.9 2 Snapshot contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 1.11 Virtual machine configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 1.12 Removing virtual machines

. . . . . . . . . 16 1.7 Creating your first virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.8 Running your virtual machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.8.5 Resizing the machine’s window . . . . . . . . . . . . . . . . . . . . . . 23 1.8.6 Saving the state of the machine . . . . . . . . . . . . . . . . . . . . . . 23 1.9 2 Snapshot contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.10 Virtual machine configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.11 Removing virtual machines

Development Trending = Unprecedented37 Machine-Learning Model* Trending = In 2015... Industry Surpassed Academia as Data + Compute + Financial Needs Rose *Machine Learning = A subset of AI where machines AI, an AI Index data provider, uses the term ‘notable machine learning models’ to designate particularly influential models within the AI/machine learning ecosystem. Epoch maintains a database of 900 Academia Era 2015-today: Industry Era Global Notable Machine Learning Models by Sector – 2003-2024, per Stanford HAI Annual New Notable Machine-Learning Models AI Development Trending = Unprecedented38