Search Results for "gpu hardware"
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Showing 10 open source projects for "gpu hardware"
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Skiko
Kotlin Multiplatform bindings to Skia
Skiko is an open-source graphics library from JetBrains that provides lightweight, cross-platform bindings for the Skia graphics engine tailored specifically for Kotlin Multiplatform and Compose applications. It serves as the low-level rendering backbone for Kotlin UI frameworks like Compose for Desktop and Compose for Web, enabling smooth, GPU-accelerated 2D graphics across Windows, macOS, Linux, and other supported targets without writing native code. Skiko abstracts away platform-specific rendering details while exposing Skia’s powerful features such as high-quality text shaping, image filters, path operations, and hardware accelerated canvases, making it ideal for building rich UI components, animations, games, or custom drawing surfaces. ... -
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HLSL++
Math library using HLSL syntax with multiplatform SIMD support
HLSL++ is a header-only C++ math library designed to replicate the syntax and functionality of the HLSL shading language, making it easier for developers to write CPU-side code that mirrors GPU shader logic. It provides vector, matrix, and math operations with a syntax identical or very similar to HLSL, allowing seamless transition between shader code and application code. The library is optimized for performance and supports SIMD instructions across multiple architectures, including SSE, AVX, AVX2, AVX512, and ARM NEON, ensuring high efficiency on modern hardware. -
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ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if... -
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Codon
A high-performance, zero-overhead, extensible Python compiler
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still. The Codon framework is fully modular and extensible, allowing for the seamless integration of new modules, compiler optimizations, domain-specific languages and so on. We actively develop Codon... -
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5
bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
6
FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
...On very compute-bound settings, it can reach up to ~660 TFLOPS on H800 SXM5 hardware, while in memory-bound configurations it can push memory throughput to ~3000 GB/s. The team regularly updates it with performance improvements; for example, a 2025 update claims 5 % to 15 % gains on compute-bound workloads while maintaining API compatibility. -
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VK-GL-CTS
Khronos Vulkan, OpenGL, and OpenGL ES Conformance Tests
...These tests are essential for vendors seeking certification, as they rigorously check the correctness and completeness of driver implementations against standardized behavior. The suite contains thousands of automated tests that assess rendering accuracy, API behavior, memory usage, and performance consistency. It is widely used by GPU vendors and developers to ensure compatibility, stability, and reliability across platforms and hardware. -
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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR... -
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QtAV
A multimedia framework based on Qt and FFmpeg
QtAV is a cross-platform and high performance multimedia playback framework based on Qt and FFmpeg. Features: timeline preview, gpu decoding etc -
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10
overdrive5
AMD GPU power/fan control via ADL OverDrive5 interface
Command line tool that uses AMD ADL OverDrive5 interface to control power and fan speed of their GPU boards. Look at the Wiki page about usage. Works on Windows and Linux (if video driver is loaded).
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