Search Results for "metal"
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Showing 273 open source projects for "metal"
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tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
tt-metal, also referred to in its documentation as TT-Metalium, is Tenstorrent’s low-level software development kit for programming applications on Tenstorrent AI accelerators. The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. -
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h3-metal
MiniMax H3 inference engine for Mac computers
h3-metal is a native MiniMax-H3 inference engine for Apple Silicon focused on generating video and audio locally with Metal. It supports prompt-to-video and prompt-to-audio workflows as well as first-frame, last-frame, image, video, and audio references. An interactive terminal session keeps prompt conditioning, the diffusion transformer, and the video decoder in memory for faster repeated generations. -
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Metal.jl
Metal programming in Julia
...If you are interested in contributing to this, see this issue for more details. In practice, Metal.jl will probably work on any macOS 10.15+, and other GPUs that are supported by Metal might also function (if only partially), but such combinations are unsupported for now. -
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Savon
Heavy metal SOAP client
Heavy metal SOAP client. Savon version 2 is available through Rubygems. -
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ds4.c
DeepSeek 4 Flash local inference engine for Metal
ds4.c is a specialized local inference engine created by antirez for running DeepSeek V4 Flash models directly on Apple Silicon hardware using Metal acceleration. Unlike general-purpose inference runtimes, the project is intentionally optimized for a specific model family, enabling highly efficient execution and simplified architecture. The engine includes DS4-specific model loading, KV cache management, prompt rendering, and OpenAI-compatible server APIs for local deployment workflows. ... -
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Command & Conquer Generals: Zero Hour
Zero Hour running natively on macOS, iPhone & iPad
...The project builds on EA’s GPL v3 source release and several community porting efforts, then adds iOS and iPadOS support, engine fixes, packaging, and touch controls. Rendering moves from DirectX 8 through DXVK and Vulkan, then through MoltenVK into Apple’s Metal stack. The port supports campaign, skirmish, and Generals Challenge modes, but it does not include or distribute the original game assets. It is both a playable classic RTS port and a detailed engineering reference for bringing old Windows games to modern Apple devices. -
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TurboFieldfare
Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook
TurboFieldfare is a custom Swift and Metal runtime for running the instruction-tuned Gemma 4 26B-A4B model on Apple Silicon Macs with limited memory. Instead of loading the entire model, it keeps the shared core and KV cache in RAM while streaming only the routed experts required for each token from SSD. This approach reduces active memory use to roughly 2 GB while the installed model occupies about 14.3 GB of storage. -
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Madeira
Run x86-64 Windows PC games on jailed iOS via FEX-Emu + Wine + DXMT
Madeira is an experimental compatibility project for running x86-64 Windows PC games on a non-jailbroken iPhone. It combines Wine using ARM64EC, FEX-Emu for x86-64 to ARM64 translation, and DXMT for Direct3D 11 to Metal graphics conversion. All major components operate inside a single Mach process, with wineserver adapted to run as a thread. The project requires JIT execution, which on iOS is enabled through debugger attachment rather than ordinary App Store distribution. Games such as Thumper and ULTRAKILL have reached playable states, while other titles vary widely in performance and stability. ... -
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stable-diffusion.cpp
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference
...It enables text-to-image and image-to-image generation, supports a growing set of models like SD1.x, SD2.x, SDXL, SD-Turbo, Qwen Image, and more, and is continually updated with support for cutting-edge model variants including video and image editing models. The project is built on the ggml backend, which allows efficient execution on CPUs and GPUs via backends like CUDA, Vulkan, Metal, OpenCL, and SYCL, making it suitable for everything from desktops to mobile devices. It includes options for ControlNet, LoRA models, upscaling via ESRGAN, and advanced sampling techniques, giving developers and users a rich toolkit for creative workflows. -
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Azure Linux
General purpose Linux OS for Azure
Azure Linux is Microsoft’s open-source Linux distribution built and optimized for Azure environments. It is designed to provide a secure and reliable operating system for virtual machines, containers, and bare-metal platforms. The distribution is derived from Fedora Linux sources while adding Azure-specific engineering for cloud operations. It uses the RPM package ecosystem, which makes it familiar to administrators and developers who already work with RPM-based Linux systems. Azure Linux emphasizes hardened security, supply chain integrity, compliance readiness, and predictable lifecycle management. ... -
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Beta9
Run serverless GPU workloads with fast cold starts on bare-metal
beta9 is a platform that enables running serverless GPU workloads with fast cold starts on bare-metal servers globally. It allows developers to deploy and scale GPU-accelerated applications without managing underlying infrastructure, offering flexibility and efficiency for AI and high-performance computing tasks. beta9 supports various frameworks and provides tools for monitoring and managing deployments effectively. -
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MetalLB
A network load-balancer implementation for Kubernetes
MetalLB is a load-balancer implementation for bare metal Kubernetes clusters, using standard routing protocols. Kubernetes does not offer an implementation of network load balancers (Services of type LoadBalancer) for bare-metal clusters. The implementations of network load balancers that Kubernetes does ship with are all glue code that calls out to various IaaS platforms (GCP, AWS, Azure…). -
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Retrobios
Complete BIOS and firmware packs for RetroArch, Batocera, Recalbox
...It emphasizes simplicity and transparency, allowing developers to study and modify core boot processes at a granular level. The architecture is typically close to bare metal, requiring knowledge of assembly language and hardware interfaces. It may also serve as a foundation for building custom operating systems or experimenting with low-level system design. Overall, retrobios functions as a learning and experimentation platform for understanding foundational computing concepts. -
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Gardener
Kubernetes-native system managing the full lifecycle of Kubernetes
...Gardener was born as a solution for actual and common problems such as control on the Kubernetes stack, minimizing the TCO, infrastructures pervasiveness, operating in restricted/regulated environments or bare metal, at a massive scale. -
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Kubespray
Deploy a Production Ready Kubernetes Cluster
Can be deployed on AWS, GCE, Azure, OpenStack, vSphere, Equinix Metal (bare metal), Oracle Cloud Infrastructure (Experimental), or Baremetal. Highly available cluster. Composable (Choice of the network plugin for instance). Supports most popular Linux distributions. Continuous integration tests. The list of available docker versions is 18.09, 19.03, and 20.10. The recommended docker version is 20.10. -
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Autodesk Fusion 360
Use Autodesk Fusion 360 on Linux
Autodesk Fusion 360 is a cloud-based 3D modeling, CAD, CAM, CAE, and PCB software platform for product design and manufacturing that offers an affordable, powerful alternative to other well-known solutions on the market.But the problem is that it usually only works on systems that have Windows or macOS installed as the operating system. I'm using a Linux distribution such as openSUSE Tumbleweed and needed a solution to this problem. And so, with this nice tool, we no longer need two... -
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Colibrì
Run frontier MoE models on hardware you already own
...This architecture enables users to run models ranging from 7 billion to 2.8 trillion parameters without requiring the entire model to fit in expensive GPU memory. Written primarily in pure C, Colibrì has no core engine dependencies and can operate without a GPU, although CUDA, Metal, Vulkan, and other acceleration options can improve performance. A consistent command-line interface, OpenAI-compatible API, web dashboard, and desktop application support multiple model families, including GLM, DeepSeek, Kimi, Qwen, Inkling, and OLMoE. Colibrì also serves as an open research platform for testing model placement, caching, compression, speculative decoding, storage I/O, & more. -
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Taichi
Productive, portable, and performant GPU programming in Python
...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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MicroPython
Python implementation for microcontrollers and constrained systems
MicroPython is a lean and efficient implementation of the Python 3 programming language that includes a small subset of the Python standard library and is optimised to run on microcontrollers and in constrained environments. The MicroPython pyboard is a compact electronic circuit board that runs MicroPython on the bare metal, giving you a low-level Python operating system that can be used to control all kinds of electronic projects. MicroPython is packed full of advanced features such as an interactive prompt, arbitrary precision integers, closures, list comprehension, generators, exception handling and more. Yet it is compact enough to fit and run within just 256k of code space and 16k of RAM. ... -
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wgpu
Safe and portable GPU abstraction in Rust, implementing WebGPU API
wgpu is a safe and portable graphics library for Rust based on the WebGPU API. It is suitable for general purpose graphics and compute on the GPU. Applications using wgpu run natively on Vulkan, Metal, DirectX 11/12, and OpenGL ES; and browsers via WebAssembly on WebGPU and WebGL2. Angle is a translation layer from GLES to other backends, developed by Google. We support running our GLES3 backend over it in order to reach platforms with GLES2 or DX11 support, which aren't accessible otherwise. In order to run with Angle, "angle" feature has to be enabled, and Angle libraries placed in a location visible to the application. ... -
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qvac-fabric-llm.cpp
QVAC Fabric: cross-platform LLM inference and fine-tuning
...The project focuses on removing hardware limitations traditionally associated with LLM deployment by enabling support for a wide range of backends, including Vulkan, Metal, CUDA, and CPU, making it accessible on devices ranging from smartphones to enterprise servers. It introduces native LoRA fine-tuning capabilities that can be executed directly on consumer hardware, allowing developers to train and adapt models locally without relying on cloud infrastructure. A key innovation is its support for BitNet ternary quantized models, enabling highly efficient inference and training even on resource-constrained systems. -
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TileLang
Domain-specific language designed to streamline the development
...Developers can work at different abstraction levels while still controlling memory layout, scheduling, pipelines, and hardware-specific behavior. Current backends include CUDA, ROCm, Metal, CPU, and Huawei Ascend support. The project includes autotuning, debugging tools, layout visualization, compiler diagnostics, and an LSP for editor assistance. Kernels can be integrated with PyTorch and compiled for several modern accelerator families. TileLang aims to combine research-friendly productivity with performance close to specialized hand-tuned kernels. -
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react-native-fast-tflite
High-performance TensorFlow Lite library for React Native
...It can load and swap TensorFlow Lite models at runtime, making it useful for apps that run multiple machine learning tasks. The project supports GPU-accelerated delegates such as CoreML, Metal, and OpenGL. It is especially useful for mobile computer vision, on-device inference, and VisionCamera-based workflows that need fast local model execution. -
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OpenVINO Model Server
A scalable inference server for models optimized with OpenVINO
...The server exposes model inference via standard network protocols like REST and gRPC, allowing any client that speaks those protocols to request predictions remotely, abstracting away the complexity of where and how the model runs. It supports model deployment in diverse environments including Docker, bare-metal machines, and Kubernetes clusters, and is especially useful in microservices architectures where AI services need to scale independently. The system supports a wide range of model sources, letting you host models from local storage, remote object storage, or even pull from model hubs. -
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Hermit Kernel
A Rust-based, lightweight unikernel
Hermit Kernel is the core component of HermitCore, a Rust-based unikernel that runs directly on hypervisors or bare-metal systems to support high-performance cloud and HPC applications. This repository contains the microkernel’s implementation, optimized for running Rust applications natively in a lightweight, single-address-space environment. Hermit Kernel is designed to reduce latency and overhead by avoiding traditional OS abstractions, while still providing essential services such as scheduling, memory management, and networking. ...
