Search Results for "jit"
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Showing 87 open source projects for "jit"
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JiT
PyTorch implementation of JiT
JiT is an open-source PyTorch implementation of a state-of-the-art image diffusion model designed around a minimalist yet powerful architecture for pixel-level generative modeling, based on the paper Back to Basics: Let Denoising Generative Models Denoise. Rather than predicting noise, JiT models directly predict clean image data, which the research suggests aligns better with the manifold structure of natural images and leads to stronger generative performance at high resolution. ... -
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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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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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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. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate into the JIT runtime seamlessly. ... -
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Taichi
Productive, portable, and performant GPU programming in Python
Taichi is an open-source, embedded DSL within Python designed for high-performance numerical and physical simulations. It uses JIT compilation (via LLVM and its runtime TiRT) to offload compute-heavy code to CPUs, GPUs, mobile devices, and embedded systems. With built-in support for sparse data structures (SNode), automatic differentiation, AOT deployment, and compatibility with CUDA, Vulkan, Metal, and OpenGL ES, it empowers disciplines like simulation, graphics, AI, and robotics -
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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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Play!
Play! - PlayStation2 Emulator
...pursues compatibility incrementally, with many titles playable to varying degrees and an active compatibility tracker detailing individual game status. The project supports optimizations such as JIT code generation on compatible platforms to improve performance and offers a broad set of build targets so developers and users can experiment with different back ends and environments. -
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box64
Linux Userspace x86_64 Emulator with a twist, targeted at ARM64 Linux
Box86 lets you run x86 Linux programs (such as games) on non-x86 Linux systems, like ARM (the host system needs to be 32bit little-endian). Because box86 uses the native versions of some “system” libraries, like libc, libm, SDL, and OpenGL, it’s easy to integrate and use with most applications, and performance can be surprisingly high in some cases. Many games already work without much tweaking, for example: WorldOfGoo, Airline Tycoon Deluxe, and FTL. Many of the GameMaker Linux games also... -
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melonDS
DS emulator, sorta
melonDS aims at providing fast and accurate Nintendo DS emulation. While it is still a work in progress, it has a pretty solid set of features. Firmware boot (not direct boot) requires a BIOS/firmware dump from an original DS or DS Lite. DS firmwares dumped from a DSi or 3DS aren't bootable and only contain configuration data, thus they are only suitable when booting games directly. DS BIOS dumps from a DSi or 3DS can be used with no compatibility issues. -
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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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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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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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DeepGEMM
Clean and efficient FP8 GEMM kernels with fine-grained scaling
...It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of Experts (MoE) that require segmented matrix multiplications. One distinguishing aspect is that DeepGEMM compiles its kernels at runtime (via a lightweight Just-In-Time (JIT) module), so users don’t need to precompile CUDA kernels before installation. Despite its lean design, it includes scaling strategies (fine-grained scaling) and optimizations inspired by cutting edge systems (drawing from ideas in CUTLASS, CuTe) but in a more streamlined form. -
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Sonic JSON
A blazingly fast JSON serializing & deserializing library
A blazingly fast JSON serializing & deserializing library, accelerated by JIT (just-in-time compiling) and SIMD (single-instruction-multiple-data). -
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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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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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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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DuckStation
Fast PlayStation 1 emulator for x86-64/AArch32/AArch64
DuckStation is an simulator/emulator of the Sony PlayStation(TM) console, focusing on playability, speed, and long-term maintainability. The goal is to be as accurate as possible while maintaining performance suitable for low-end devices. "Hack" options are discouraged, the default configuration should support all playable games with only some of the enhancements having compatibility issues. A "BIOS" ROM image is required to to start the emulator and to play games. You can use an image from... -
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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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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.
