Search Results for "gpu id"
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Showing 7 open source projects for "gpu id"
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Radeon-ID
Official Mirror for AMD Domestic Community Drivers Indonesia
AMD Domestic Community Driver with Multi-Kernel Radeon Driver Release Experience enhanced performance and flexibility with our multi-kernel Radeon driver, tailored for the AMD community. 📢 Need help or have questions? Join our 24/7 Discord support channel for real-time assistance and discussions: https://discord.gg/rdnid -
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HWID Spoofer - Hardware ID Changer
The best HWID Spoofer in 2025.
TraceX is a powerful and advanced HWID Spoofer designed to bypass anti-cheat systems in games like Valorant, Apex Legends, Warzone, Fortnite, and more. It spoofs critical system identifiers such as disk serials, MAC addresses, BIOS UUIDs, motherboard and GPU IDs, and even EFI boot variables. This HWID Spoofer also includes a full system cleaner that removes traces of game activity, browser data, event logs, Xbox and Discord accounts, and network fingerprints. With deep spoofing of CPU,... -
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Hardware Serial Spoofer
An open-source tool for managing and modifying hardware ID
Hardware Identity Manager (HIM) is a powerful utility designed for advanced users, developers, and security researchers to manage the hardware identification values of their Windows-based systems. -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow.... -
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DarkMagic
This is a Custom Kernel for Redmi Note 5 Pro a.k.a Whyred [PIE]
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SW#
smith waterman, gpu, cuda, alignment
SW# (swsharp) is a library for sequence alignment based on CUDA enabled GPUs. It utilizes Hirschbergs and Ukkonens algorithm for memory efficiency and additional speed up. The library is scalable for use with multiple GPUs. Some parts of the library utilize MPI for CUDA enabled clusters. This work has been supported in part by Croatian Science Foundation under the project UIP-11-2013-7353. Database search now... -
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GPUCL is an OpenGL implementation of connected component labeling. All operations are performed fully on the GPU. Every pixel in the source image is correctly labeled with an ID and bounding boxes are computed for each detected blob.
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