Search Results for "jit compiler"
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Showing 41 open source projects for "jit compiler"
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1
JITWatch
Log analyser / visualiser for Java HotSpot JIT compiler
Log analyser / visualiser for Java HotSpot JIT compiler. Inspect inlining decisions, hot methods, bytecode, and assembly. View results in the JavaFX user interface. -
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XLS
XLS: Accelerated HW Synthesis
XLS is an open-source toolkit for building high-level hardware with a modern compiler stack that spans from a functional DSL to optimized IR and hardware generation. 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. ... -
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. -
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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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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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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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WebAssembly Micro Runtime
WebAssembly Micro Runtime (WAMR)
...Developed under the Bytecode Alliance, WAMR emphasizes a small memory footprint and high configurability, enabling it to operate effectively even in constrained hardware environments. The runtime supports multiple execution modes, including interpreter, Ahead-of-Time (AOT) compilation, and Just-in-Time (JIT) compilation, allowing developers to balance performance and portability depending on their needs. WAMR also provides near-native execution speed through its optimized compilation strategies, making it suitable for performance-critical applications. It includes a modular architecture with components such as a runtime core, an AOT compiler, and application frameworks that facilitate real-world deployment scenarios. -
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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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LatticeQCD.jl
A native Julia code for lattice QCD with dynamical fermions in 4D
This code enables you to perform lattice QCD calculations! A native Julia code for Lattice QCD. -
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netsniff-ng
A Swiss army knife for your daily Linux network plumbing
netsniff-ng is a free Linux networking toolkit, a Swiss army knife for your daily Linux network plumbing if you will. Its gain of performance is reached by zero-copy mechanisms, so that on packet reception and transmission the kernel does not need to copy packets from kernel space to user space and vice versa. Our toolkit can be used for network development and analysis, debugging, auditing, or network reconnaissance. -
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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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Compact embeddable JIT compiler that reads C headers and compiles to x86 machine code. Executes directly in memory or creates DLLs and EXE files. Supports overloading and OOP. Currently available for MS platforms. 64bit in progress
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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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BetaML.jl
Beta Machine Learning Toolkit
...If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its implementation. Thanks to its JIT compiler, Julia is indeed in the sweet spot where we can easily write models in a high-level language and still have them running efficiently. -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can... -
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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... -
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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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XORT Compiler
XORT compiler
Experimental compiler for XORT programming language. This is an investigation project developed during 2008-2014 years. Compiler and virtual machine were written from scratch. The compiler and virtual machine is based on minimalist approach: to implement in compiler only features, that allow compiler to compile itself. Key Features ARC based memory management (no operators new and delete) no pointers and pointer arithmetic implicit type casting for simple types no casting for complex types hi-level XORT assembler keeps types information for XVM native interface to system functions and 3rd party dlls Application easy scripting support education Future plans JIT code generation in XVM AOT code generation in compiler add OOP features to language: access modifiers, inheritance templates support IDE with debugger -
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RVVM
The RISC-V Virtual Machine
...It implements a fully spec-compliant RISC-V architecture, supporting modern instruction sets and extensions while maintaining a lean and modular codebase. One of its most notable features is its tracing JIT compiler, which enables significantly faster execution compared to traditional emulation approaches like QEMU’s TCG. The system is capable of running full operating systems such as Linux, FreeBSD, and OpenBSD, as well as supporting userland emulation for running RISC-V applications directly on foreign hosts. RVVM includes a rich virtual hardware environment, including networking, storage devices, and input systems, allowing for realistic system-level emulation. -
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ts-node
TypeScript execution and REPL for node.js
...Installing modules locally allows you to control and share the versions through package.json. TS Node will always resolve the compiler from cwd before checking relative to its own installation.ts-node exports a create() function that can be used to initialize a TypeScript compiler that isn't registered to require.extensions, and it uses the same code as register. ts-node supports a variety of options which can be specified via tsconfig.json, as CLI flags, as environment variables, or programmatically. -
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WebVM
Virtual Machine for the Web
...It is designed to be Linux ABI-compatible, allowing unmodified Linux binaries to run seamlessly without requiring server-side infrastructure. Powered by the CheerpX virtualization engine, WebVM includes an x86-to-WebAssembly JIT compiler, a virtual file system, and a Linux syscall emulator, enabling realistic execution of applications. The system can run a full Debian distribution, including development tools, graphical interfaces, and command-line utilities. One of its most notable features is its serverless design, meaning all computation occurs locally in the browser, enhancing privacy and reducing dependency on external servers. ... -
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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. -
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gremlin-scheme
The Gremlin Scheme Project
gremlin-scheme is a scheme system for translating or compiling Scheme code to other assemblers and languages. It is mainly developed for macOS X. There is some sort of transparency for the code for the Amiga 2000 (workbench 2.x, vbcc compiler.) There is a symbol API where you can set variables with the "define" keyword, the lambda API is in place but it does not parse fully. Everything is clean to develop a Scheme from, you just need to plug in parsing and JIT compilation. The GameBoy assembler is in as a reference. -
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tailwind-rn
Use Tailwind CSS in React Native projects
...A small CLI tool reads the CSS file produced by Tailwind and transforms it into a JSON file that tailwind-rn can consume, with support for watching and rebuilding whenever Tailwind’s output changes. The library supports Tailwind 3.x and works with the JIT compiler, meaning you can use modern Tailwind utilities in mobile layouts. It is framework-agnostic within the React Native ecosystem and can be used with plain React Native, Expo, and other toolchains. The project is actively used and has issue discussions covering integration with storybook, Prettier’s Tailwind plugin, custom themes, and more.