Search Results for "jit"
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Showing 53 open source projects for "jit"
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Criterium
Benchmarking library for clojure
Criterium is a robust benchmarking library for Clojure that addresses common statistical and JIT-related issues. It provides accurate timings through warm-up, garbage collection control, and statistical summaries—making microbenchmarking more reliable than using time. Statistical processing of multiple evaluations. Inclusion of a warm-up period, designed to allow the JIT compiler to optimise its code. Purging of gc before testing, to isolate timings from GC state prior to testing. ... -
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Mercurius
Implement GraphQL servers and gateways with Fastify
Mercurius is a GraphQL adapter for Fastify. Caching of query parsing and validation. Automatic loader integration to avoid 1 + N queries. Just-In-Time compiler via graphql-jit. Federation support via @mercuriusjs/federation, including Subscriptions. Gateway implementation via @mercuriusjs/gateway, including Subscriptions. Batched query support. Customisable persisted queries. -
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XLS
XLS: Accelerated HW Synthesis
...At the front end, DSLX lets you describe algorithms with strong typing and familiar control flow while remaining synthesis-friendly. The compiler lowers DSLX into a rich intermediate representation, applies aggressive optimization and scheduling passes, and can either JIT the design for software simulation or emit Verilog for FPGA/ASIC flows. A key idea is “software-style” iteration: fast, deterministic simulation via the JIT encourages test-driven development and property checking before committing to RTL. XLS also provides tooling for pipelining, state insertion, and formal equivalence checks between different stages, giving developers confidence as designs evolve. ... -
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Numba CUDA Target
The CUDA target for Numba
Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. -
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Fury
A blazing fast multi-language serialization framework
Fury is a blazing-fast multi-language serialization framework powered by jit(just-in-time compilation) and zero-copy, providing up to 170x performance and ultimate ease of use. Based on efficient JIT, struct deserialization can get 170x speed up compared to other serialization frameworks. In serialization scenarios, Fury can achieve a 100x speed up compared to traditional serialization frameworks. If you use Java clusters on a large scale, this will save a lot of computing resources. -
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Flax
Flax is a neural network library for JAX
...Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging and compilation model. Flax emphasizes composability: optimizers, training loops, and checkpointing are provided as examples or utilities rather than monolithic frameworks, encouraging research-friendly customization. ... -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. ... -
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MIR
A lightweight JIT compiler based on MIR
MIR means Medium Internal Representation. MIR project goal is to provide a basis to implement fast and lightweight interpreters and JITs. Plans to try MIR light-weight JIT first for CRuby or/and MRuby implementation. Each module can contain functions and declarations and data. Each function has a signature (parameters and return types), local variables (including function arguments) and instructions. Each local variable has a type which can be only a 64-bit integer, float, double, or long double. Each instruction has an opcode and operands. ... -
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CUDA Python
Performance meets Productivity
...It acts as a metapackage composed of multiple submodules that provide both high-level and low-level access to CUDA functionality, including runtime APIs, driver APIs, and JIT compilation tools. The project is designed to simplify GPU programming by offering Pythonic abstractions while still exposing the full power of CUDA for advanced users. It integrates tightly with the broader Python GPU ecosystem, including Numba for kernel compilation and CCCL for parallel primitives, allowing developers to write performant code without leaving Python. ... -
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Proxy
Proxy: Next Generation Polymorphism in C++
...There are many drawbacks in this mechanism, including life management (because each object may have a different size and ownership) and reflection (because it is hard to balance between usability and memory allocation). To workaround these drawbacks, some languages like Java or C# choose to sacrifice performance by introducing GC to facilitate lifetime management, and JIT-compile the source code at runtime to generate full metadata. We improved the theory and implemented it as a C++ library without sacrificing performance, proposing to merge it into the C++ standard. -
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Numba
NumPy aware dynamic Python compiler using LLVM
Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed. -
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RustPython
A Python Interpreter written in Rust
RustPython is an implementation of the Python programming language written in Rust. Its goal is to provide a fast, embeddable, and secure interpreter that can be integrated into Rust applications or used standalone. Because it’s in Rust, it benefits from memory safety and modern tooling, allowing developers to compile Python into efficient binaries or embed it as a scripting engine in Rust projects. The interpreter aims to support the Python standard library, dynamic typing, garbage... -
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LÖVR
Lua Virtual Reality engine
...Out of the box you get fast stereo rendering, VR controllers, hand tracking, haptics, spatial audio, 3D physics, PBR materials, SDF fonts, multiplayer, and more. The entire engine is 1MB and runs on LuaJIT, the fastest JIT compiler round these parts. Projects are just folders with scripts and assets in them, organized however you want. -
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RLax
Library of JAX-based building blocks for reinforcement learning agents
...Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as value-based, policy-based, and model-based approaches. RLax is fully JIT-compilable with JAX, enabling high-performance execution across CPU, GPU, and TPU backends. The library implements tools for Bellman equations, return distributions, general value functions, and policy optimization in both continuous and discrete action spaces. It integrates seamlessly with DeepMind’s Haiku (for neural network definition) and Optax (for optimization), making it a key component in modular RL pipelines. -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
Shumai is an experimental differentiable tensor library for TypeScript and JavaScript, developed by Facebook Research. It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. It allows seamless integration of machine... -
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Halide
A language for fast, portable data-parallel computation
...It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an in-memory representation of a Halide pipeline using Halide's C++ API. This representation can then be compiled to an object file, or a JIT-compile and run in the same process. Halide also comes with a Python binding, allowing the writing of Halide embedded in Python without C++. -
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Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. ... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural... -
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Objeck
Simple ⇒ Object-Oriented ⇒ Functional
Objeck is an object-oriented programming language with functional features. Objeck emphasizes, expression, simplicity, portability, and scalability. The programming environment consists of a compiler, virtual machine, and command line debugger with IDE plugins. -
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FrenchKiss.js
The blazing fast lightweight internationalization (i18n) module
...It provides a simple and really fast solution for handling internationalization. FrenchKiss is by now, the fastest i18n JS package out there, working 5 to 1000 times faster than any others by JIT compiling the translations, try it by running the benchmarks. -
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PI-Based Image Encoder / Converter
Python code able to convert / compress image to PI (3.14, π) Indexes
...ZIP also include 16 MB file with 16,7 mil numbers of PI Benchmark(Single-Thread): Hardware & Environment Apple Silicon: Apple M2 (Mac mini/MacBook) x86_64 Platform: Intel Core Ultra 5 225F (Arrow Lake, 10 Cores) OS 1: Fedora 43 (GNOME) OS 2: Windows 11 Pro (23H2/24H2) Software: Python 3.14.3 + Numba JIT (latest) Results (Lower is better) Platform / OS CPU Time (Seconds) macOS (Native) Apple M2 52.151311 s (in default setup) Fedora Linux Intel Core Ultra 5 225F 58.536457 s (in default Power Management: Balanced) Windows 11 Intel Core Ultra 5 225F 59.681427 s (important! Power Management set as High Performance .. in Balanced is slow) -
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ts-node
TypeScript execution and REPL for node.js
It JIT transforms TypeScript into JavaScript, enabling you to directly execute TypeScript on Node.js without precompiling. This is accomplished by hooking node's module loading APIs, enabling it to be used seamlessly alongside other Node.js tools and libraries. Automatic defaults to match your node version, integrate with test runners, debuggers, and CLI tools, compatible with pre-compilation for production. -
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MyJIT is a small library allowing to (JIT) compile intermediate language into the machine code and subsequently execute it.
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Ravi Programming Language
Ravi is a dialect of Lua, featuring limited optional static typing
Ravi Programming Language is a derivative of Lua 5.3 with limited optional static typing and MIR-based JIT compiler. Ravi is a derivative/dialect of Lua with limited optional static typing and JIT/AOT compilers. The name Ravi comes from the Sanskrit word for the Sun. Lua is perfect as a small embeddable dynamic language so why a derivative? Ravi extends Lua with static typing for greater performance under JIT compilation. However, static typing is optional and therefore Lua 5.3 programs are also valid Ravi programs. ... -
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CoreCLR
Runtime for .NET Core
CoreCLR is the runtime for .NET Core, an open source, general purpose development platform maintained by Microsoft and the .NET community. It is a cross-platform runtime for cloud, IoT, and desktop apps and includes a just-in-time compiler called RyuJIT.
