Search Results for "gpu-z"
Sort By:
Showing 113 open source projects for "gpu-z"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
1
A to Z Resources for Students
Curated list of resources for developers
A to Z Resources for Students is a curated directory of learning materials, developer tools, programs, events, and career opportunities for students and early-career technologists. It helps users discover resources for learning programming languages, frameworks, AI, machine learning, cybersecurity, mobile development, and other technical fields. -
2
Z-Stack Firmware
Compilation instructions and hex files for Z-Stack firmwares
...Compilation guidance is also included for users who need to produce or customize firmware for supported targets. The repository is commonly useful when preparing Zigbee adapters for ecosystems that depend on TI Z-Stack firmware. -
3
cuDF
GPU DataFrame Library
...The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. -
4
cuda-oxide
cuda-oxide is an experimental Rust-to-CUDA compiler
...Its main value is giving Rust developers a more direct path into NVIDIA GPU kernels while preserving familiar Rust syntax and tooling concepts. -
Build Data Resilience - Take the Assessment TodayIs your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
-
5
jamesob's guide to running SOTA LLMs
Everything I know about running LLMs locally
jamesob's guide to running SOTA LLMs is a practical guide and configuration repository for running high-end language models on local hardware. It documents one developer’s local LLM setup, including hardware choices, GPU layout, storage, PCIe switches, kernel settings, and serving workflows. The repository compares budget levels ranging from dual RTX 3090 systems to high-end multi-GPU workstations with very large VRAM pools. It includes ready-to-run serving configurations for selected models and local speech-to-text workloads. The guide focuses on real deployment details such as Docker containers, model weight storage, GPU peer-to-peer behavior, and agentic workload performance. ... -
6
Khronos KTX
KTX (Khronos Texture) Library and Tools
KTX-Software is a suite of tools and libraries for working with Khronos Texture (KTX) files, designed and maintained by the Khronos Group. KTX is a container format for storing textures that are optimized for GPU upload, supporting modern formats like Basis Universal and ASTC. This repository includes tools for creating, validating, inspecting, and converting KTX and KTX2 files, making it essential for developers working in 3D engines, games, and visualization tools where texture streaming and compression are key. -
7
CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. CuPy is highly compatible with NumPy, serving as a drop-in replacement in most cases. CuPy is very easy to install through pip or through precompiled binary packages called wheels for recommended environments. ... -
8
CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
...By unifying these components, CCCL reduces duplication and improves developer productivity while maintaining performance across different GPU architectures. -
9
PortableGL
An implementation of OpenGL 3.x-ish in clean C
PortableGL is a single-header, software-only implementation of a subset of OpenGL (specifically the GL 2.1 pipeline), designed to run entirely on the CPU. This lightweight graphics library allows OpenGL-style rendering without GPU acceleration, making it ideal for educational use, debugging, embedded systems, and retro-style software rendering. Because it mirrors OpenGL syntax and design, it can act as a drop-in CPU renderer for testing or deploying 3D graphics on platforms without GPU support. -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
-
10
MuJoCo Playground
An open source library for GPU-accelerated robot learning
MuJoCo Playground, developed by Google DeepMind, is a GPU-accelerated suite of simulation environments for robot learning and sim-to-real research, built on top of MuJoCo MJX. It unifies a range of control, locomotion, and manipulation tasks into a consistent and scalable framework optimized for JAX and Warp backends. The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups. ... -
11
DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP addresses that by providing optimized GPU kernels and efficient dispatch/combining logic. ... -
12
Faiss
Library for efficient similarity search and clustering dense vectors
...It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes that the instances are represented as vectors and are identified by an integer, and that the vectors can be compared with L2 (Euclidean) distances or dot products. Vectors that are similar to a query vector are those that have the lowest L2 distance or the highest dot product with the query vector. ... -
13
libplacebo
Official mirror of libplacebo
libplacebo is a flexible, high-performance graphics library built on top of Vulkan, designed to provide reusable GPU-accelerated components for media applications. It originated as a core part of the rendering pipeline for the mpv media player and has since grown into a standalone library used for tone mapping, dithering, color space conversion, and more. libplacebo is ideal for developers looking to integrate sophisticated video rendering and post-processing into their own applications with full control over shaders and rendering stages. -
14
Images.jl
An image library for Julia
...Julia is well-suited to image processing because it is a modern and elegant high-level language that is a pleasure to use, while also allowing you to write "inner loops" that compile to efficient machine code (i.e., it is as fast as C). Julia supports multithreading and, through add-on packages, GPU processing. JuliaImages is a collection of packages specifically focused on image processing. It is not yet as complete as some toolkits for other programming languages, but it has many useful algorithms. It is focused on clean architecture and is designed to unify "machine vision" and "biomedical 3d image processing" communities. -
15
webgl-plot
A high-Performance real-time 2D plotting library based on native WebGL
...Unlike traditional canvas or SVG-based charting libraries, webgl-plot is optimized for streaming and dynamic updates, making it ideal for oscilloscope-style data, biomedical signals, or any application where data updates hundreds of times per second. Its minimal memory footprint and GPU acceleration ensure excellent performance even with tens of thousands of data points, and its simple API allows developers to get started quickly. -
16
RLax
Library of JAX-based building blocks for reinforcement learning 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. -
17
Face Alignment
2D and 3D Face alignment library build using pytorch
...However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. While not required, for optimal performance(especially for the detector) it is highly recommended to run the code using a CUDA-enabled GPU. While here the work is presented as a black box, if you want to know more about the intrisecs of the method please check the original paper either on arxiv or my webpage. -
18
Contour
Modern C++ Terminal Emulator
contour is a modern and actually fast, modal, virtual terminal emulator, for everyday use. It is aimed at power users with a modern feature mindset. Available on all 4 major platforms, Linux, OS/X, FreeBSD, Windows. GPU-accelerated rendering. Font ligatures support (such as in Fira Code). Unicode: Emoji support (-: 🌈 💝 😛 👪 - including ZWJ, VS15, VS16 emoji :-) Unicode: Grapheme cluster support. Bold and italic fonts. High-DPI support. Vertical Line Markers (quickly jump to markers in your history!) Vi-like input modes for improved selection and copy'n'paste experience and Vi-like scrolloff feature. ... -
19
Tracy Profiler
Frame profiler
...Tracy supports profiling CPU (Direct support is provided for C, C++, Lua and Python integration. At the same time, third-party bindings to many other languages exist on the internet, such as Rust, Zig, C#, OCaml, Odin, etc.), GPU (All major graphic APIs: OpenGL, Vulkan, Direct3D 11/12, OpenCL.), memory allocations, locks, context switches, automatically attribute screenshots to captured frames, and much more. -
20
FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. ... -
21
Floem
A native Rust UI library with fine-grained reactivity
Floem is a cross-platform GUI framework for Rust. It aims to be extremely performant while providing world-class developer ergonomics. Supporting both GPU and CPU rendering, Floem gives you performance that's closest to bare metal. Also primitives are provided to help the developer to write performant UI code without too much effect. -
22
GPUPixel
Real-time image and video processing library similar to GPUImage
GPUPixel is a real-time image and video processing library written in C++11, based on OpenGL/ES. It offers functionalities similar to GPUImage, including built-in beauty filters, enabling efficient processing and rendering of visual effects on images and videos. -
23
ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
24
Perfetto
Production-grade client-side tracing, profiling, and analysis
...It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. It integrates natively with Android (replacing older atrace/Systrace paths) and can sit alongside custom instrumentation in apps or services through its SDKs. -
25
FairChem
FAIR Chemistry's library of machine learning methods for chemistry
...Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU.
