Search Results for "cuda gpu memtest windows"
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Showing 16 open source projects for "cuda gpu memtest windows"
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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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rembg
Rembg is a tool to remove images background
Rembg is a powerful tool that utilizes AI (specifically U^2-Net) to automatically remove backgrounds from images, offering a streamlined command-line interface and Docker support. It's ideal for batch processing and integrates smoothly into workflows -
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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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Warlock-Studio
AI Suite for upscaling, interpolating & restoring images/videos
v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system... -
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Imaging Instruments
High-performance image processing C++ application for Windows Desktop
Imaging Instruments is a high-performance image processing application crafted for efficiency and designed to deliver powerful and reliable image manipulation capabilities. Developed using the Model-View-Controller (MVC) architecture, Imaging Instruments harnesses the full potential of modern technologies, combining C++, Qt6, CUDA-C, and OpenCV to deliver a powerful and seamless experience for both professionals and enthusiasts. With multi-threading support via OpenMP and GPU acceleration... -
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CIRT
CIRT - CUDA Interactive Ray Tracer
CIRT is an implementation of PRTP (Programmable Ray Tracing Pipeline). Mainly it is to be used as a ray-tracing equivalent of OpenGL. It allows the user to implement various ray-tracing related algorithms. -
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Imaging Instruments Lite
Image processing App for Windows Desktop
Imaging Instruments lite is a comprehensive image processing application developed following the Model-View-Controller (MVC) design pattern, utilizing Python, Tkinter, and OpenCV. It provides users with image manipulation capabilities, leveraging multi-threading with OpenMP and GPU acceleration using CUDA-C. Fueled by yerba mate and a passion for coding. Created by Agustin Tortolero. website: https://agustintortolero.pythonanywhere.com/ Source code:... -
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Stable Diffusion in Docker
Run the Stable Diffusion releases in a Docker container
Run the Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint. Run the Stable Diffusion releases on Huggingface in a GPU-accelerated Docker container. By default, the pipeline uses the full model and weights which requires a CUDA capable GPU with 8GB+ of VRAM. It should take a few seconds to create one image. On less powerful GPUs you may need to modify some of the options; see the Examples section for more details. If you lack a... -
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CUDA Pathtracer
GPU Raytracer from scratch in C++/CUDA
GPU-Raytracer is a high-performance, real-time ray tracing engine implemented using OpenGL compute shaders. It demonstrates the power of modern GPU architectures to handle complex lighting calculations, reflections, shadows, and global illumination in real-time. This project is educational and experimental, providing insight into GPU parallelism and real-time rendering techniques. Its clean and modular C++ structure makes it a great reference for students and graphics developers alike. -
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waifu2x-cpu-torch-vks
waifu2x fork without CUDA
The original is here: https://github.com/nagadomi/waifu2x Differences: - CPU only, no CUDA needed; - double-precision version; - GPU and CPU-trained models (on the fly conversion in memory); - adapted for Lua v5.2 (works with Torch 7 on x32 Ubuntu). 31-12-2016: - removed unneeded data copies, left from CUDA processing; - removed large duplicate files (see "ReadMe" before use). -
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A GUI interface to a tool for generating SSBumps (Self Shadowed Bump Maps). Includes a CUDA GPU rendering extension.
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VolTK
A Lightweighted Toolkit For Volume Rendering
A Lightweighted Toolkit For Volume Rendering Project Started by Fei Yang Provide both CPU based and GPU (CUDA) based volume rendering. See http://www.fei-yang.org/?page_id=12 for complete descriptions and package downloads VolTK is a free C++ Toolkit that implements a tri-layer volume rendering framework, which is designed to meet the requirements of both algorithm research and application assemblage. Features * Tri-layer volume rendering * CPU implementation: multi-threading supported * GPU implementation: CUDA based implementation * CPU-GPU correspondance * Both low level interfaces and high level interfaces are provided * Replace the components easily with your own design * Various rendering modes: MIP/Isosurface/Full volume rendering * Endoscopy interaction mode implemented * Pre-integration supported * Cross platform (windows and RHEL tested) -
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Fractron 9000 is a GPU accelerated fractal flame renderer for Windows. Requires a video card that supports OpenGL 2.0 (OpenCL or CUDA recommended). Also Requires Microsoft .NET framework version 2.0.
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Renderer for flam3 cosmic recursive fractal flames implemented on GPU. Requires a CUDA-capable graphics card.
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A fast JPEG2000 encoder running on CUDA-capable GPUs. Supports lossless and lossy encoding. Both commandline tool with GUI and CUDA/C++ library. Visit >> http://cuj2k.sourceforge.net << for further information.
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it decodes jpeg file in gpu with cuda and maps it as direct3d texture I wrote this as a proof of concept, Who wishes to continue can continue.....
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