Search Results for "gpu processing"
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Showing 16 open source projects for "gpu processing"
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NVIDIA Linux Open GPU Kernel Module
NVIDIA Linux open GPU kernel module source
This is the source release of the NVIDIA Linux open GPU kernel modules, version 530.41.03. Note that the kernel modules built here must be used with GSP firmware and user-space NVIDIA GPU driver components from a corresponding 530.41.03 driver release. Currently, the kernel modules can be built for x86_64 or aarch64. If cross-compiling, set these variables on the make command line. Any reasonably modern version of GCC or Clang can be used to build the kernel modules. -
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ODM
A command line toolkit to generate maps, point clouds, 3D models
...It can process photographs captured by drones, balloons, kites, and other aerial platforms. Outputs include classified point clouds, textured 3D models, georeferenced orthophotos, and digital elevation models. The processing pipeline integrates specialized open-source projects for reconstruction, meshing, geospatial conversion, and point-cloud processing. ODM runs on Windows, macOS, and Linux and is commonly deployed through Docker. GPU acceleration is available for selected feature-extraction workloads. NodeODM can expose the processing engine over a network for integration with other applications. -
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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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Scalene
High-performance CPU, GPU, and memory profiler for Python
Scalene is a high-performance CPU, GPU and memory profiler for Python that does a number of things that other Python profilers do not and cannot do. It runs orders of magnitude faster than other profilers while delivering far more detailed information. Once Scalene has profiled your program, it will launch a web browser with an interactive user interface (all processing is done locally). -
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FlashKDA
High-performance Kimi Delta Attention kernels
FlashKDA is an open-source library of high-performance CUDA kernels for Kimi Delta Attention, implemented on NVIDIA CUTLASS. It is intended to accelerate the forward pass used by KDA-based language models on modern NVIDIA GPUs. The package integrates with flash-linear-attention and can be selected automatically as the backend for chunk_kda during inference. It supports recurrent state input and output, variable-length batches, internal gating, query-key normalization, and beta activation.... -
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PyMapStitcher-3---Cuda-Maps-Downloader
A low ram maps downloader to keep your ram free.
PyMapStitcher 3 is a desktop application for downloading, stitching, and exporting very large satellite map areas as GeoTIFF/BigTIFF files. The software supports GPU acceleration with NVIDIA CUDA and CuPy, direct GeoTIFF georeferencing, WebView-based map selection, and high-performance tile processing for large-scale mapping workflows. -
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Roblox Shaders
Roblox Shader – Download on Any GPU
Roblox Shader – Universal Graphics Enhancement for All GPUs Roblox Shader is a high-performance, universal shader mod designed to enhance Roblox graphics with realistic lighting, shadows, and post-processing effects. This shader pack is optimized for all graphics cards, including NVIDIA, AMD, and Intel GPUs, ensuring compatibility across virtually any system. Whether you're looking to improve Roblox visuals with better lighting or want a more immersive gaming experience, Roblox Shader... -
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FastoCloud PRO
IPTV/NVR/CCTV/Video cloud https://fastocloud.com
IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch Mozaic Many Outputs Physical Inputs Streaming Protocols File Formats Presets Vods/Series server-side support Pay per view channels Channels on demand HTTP Live Streaming (HLS) server-side support Public API, client server communication via JSON RPC Protocol gzip compression Deep learning video analysis Supported deep learning frameworks: Tensorflow NCSDK Caffe ML Hardware: -
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GPUImage 2
Framework for GPU-accelerated video and image processing
GPUImage 2 is the second generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac, iOS, and now Linux. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. ... -
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GPU, a Global Processing Unit
A framework for distributed computing
An extensible framework for distributed computing on P2P grids. We support peaceful free and open research and build an internet supercomputer. We render movies, solve Eternity puzzles, predict climate and improve a ~30 GHz cluster of clients. -
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mapgraph
Massively Parallel Graph processing on GPUs -- now part of Blazegraph
Mapgraph is SYSTAP’s disruptive new technology to exploit the main memory bandwidth advantages of GPUs. The early work was co-developed with the University of Utah SCI Institute and has its pedigree in the UINTAH software running on over 750M cores on the TITAN Super Computer. Today, SYSTAP has commercialized this technology into it’s Blazegraph Accelerator and Blazegraph HPC products. Checkout our options for GPU acceleration of graphs or contact us to learn more: ... -
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DistributedCL is a middleware that provides location-transparent GPU processing to applications developed using the OpenCL API. Moved to GitHub. https://github.com/andrelrt/distributedcl
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OpenShader
Open architecture GPU simulator and implementation
Documentation, simulator, compiler, and Verilog implementation of a completely open-architecture graphics processing unit. This design is intended for academic and commercial purposes. The first step is to develop a detailed GPU simulator and compiler. The second step is to implement the GPU in synthesizable Verilog. The third step is to develop a feedback loop between the simulator and implementation, allowing power, performance, and reliability aspects of the hardware to feed back into ever more detailed and accurate simulations of a complete GPU. ... -
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GPUBench2 is a cross platform suite to analyze the performance of GPU( Graphics Processing Unit). GPUBench2 will gather of state-of-the-art parameters from different interfaces ( OpenGL, Cg, CUDA) available.
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The GWO library is numerical calculation library for the diffraction integrals using a GPU (Graphics Processing Unit). If optics engineers and researchers have no knowledge of GPU, the GWO library provides them with the GPU calculation power easily.
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This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.
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