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Just-in-time compilation

Assess

Techniques

A runtime optimization technique that compiles code to native machine code while the program is running.

Why it's here

Placed in Assess: 8 article(s) of evidence from 2 source(s), led by research-stage coverage, with 1 in the last 30 days. Confidence 59%.

Evidence (8)

  • 8Hacker News·10/9/2026model_release
    Python 3.15 stable release

    Python 3.15.0 has been released as the new stable major version of the language, adding interpreter, typing, standard library, and C API improvements. The release also includes a significantly upgraded experimental JIT, updated default behaviors such as UTF-8 encoding, and notes a macOS 27.0 Tkinter compatibility issue.

  • 5InfoQ·8/27/2026research
    Using Numba and GPUs to speed up Python in financial modeling

    Chad Schuster describes how financial-services teams can combine Python’s development speed with near C-like performance using Numba JIT compilation and GPUs. He highlights actuarial modeling results, including performance gains of up to 750x, along with trade-offs such as type inference issues, object-oriented programming limits, and compilation overhead.

  • 6Hacker News·8/23/2026research
    Building a JIT Compiler That Compiles in 5 Microseconds

    The article describes how a Rust-based database project, pgrust, uses AI assistance to build a just-in-time compiler that targets assembly directly and compiles code in about 5 microseconds. It argues that this speed makes it practical to JIT-compile every SQL query, and uses a simple regex engine as the example implementation.

  • 5Hacker News·8/22/2026research
    AI-assisted software could make performance tuning cheaper and more adaptive

    The article argues that performance engineering is becoming much cheaper and more accessible because LLMs can help generate specialized optimizations that were previously too costly to build. It illustrates the point with a regex engine experiment, where an AI-assisted native AOT approach showed notable speedups on longer searches but also introduced workload-specific tradeoffs.

  • 5InfoQ·8/5/2026research
    Automating JIT Retrofits for C Interpreters

    Laurence Tratt presents yk, an open-source meta-tracing JIT compiler framework designed to speed up C-based language interpreters with minimal code changes. The talk covers how tracing, optimization hints, and deoptimization work together to improve interpreter performance while keeping fallback to the interpreter manageable.

  • 5InfoQ·8/3/2026framework_update
    HubSpot Redesigns JITA Authorization with a Rule Engine

    HubSpot redesigned its Just-In-Time Access authorization system around a rule engine architecture. The new approach evaluates access requests through independent rules in a directed acyclic graph and adds structured decision metadata, observability, and governance workflows.

  • 4InfoQ·8/3/2026framework_update
    WebAssembly on the JVM and the Shift to Endive

    Andrea Peruffo discusses how WebAssembly is evolving beyond the browser and gaining traction on the server-side JVM. The episode covers runtime performance improvements, including the move from interpreters to JIT compilation, and highlights production uses such as edge computing and modular plugins.

  • 5Hacker News·6/29/2026research
    Game Boy Emulator JITs to WebAssembly to Run Faster in Browsers

    A developer built WATaBoy, a Game Boy emulator that compiles SM83 instructions to WebAssembly instead of relying only on an interpreter. The project explores whether piggybacking on browser JIT support can outperform a native interpreter, especially in environments like iOS where direct JIT compilation is restricted. The post presents the approach as a proof of concept and performance benchmark.