Search Results for "cpu benchmark linux" - Page 3
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Showing 74 open source projects for "cpu benchmark linux"
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights... -
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the... -
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Yandex Tank
Load and performance benchmark tool
Yandex.Tank is an extensible open-source load testing tool for advanced Linux users which is especially good as a part of an automated load testing suite. Different load generators are supported. Evgeniy Mamchits' phantom is a very fast (100 000+ RPS) shooter written in C++ (default) JMeter is an extendable and widely known one. BFG is a Python-based generator that allows you to write your load scenarios in Python. Experimental Golang generator: pandora. Performance analytics backend... -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
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RefineNet
RefineNet: Multi-Path Refinement Networks
RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets... -
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coNCePTuaL
DSL for writing communication benchmarks
coNCePTuaL is a toolset for rapidly generating portable, readable, and reproducible network-performance tests. coNCePTuaL can perform the equivalent of many pages of C code with just a few mouse clicks or lines of code in a domain-specific language. -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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vEMan - VMware ESX/ESXi Manager
An unofficial VMware® ESX/ESXi Manager for Linux
vEMan - [v]Mware [E]SX [Man]ager provides a GUI for managing ESX servers natively from within your Linux desktop without the need to use Windows vSphere® anymore! Support vEMan development for v2.0 by gofundme! http://www.gofundme.com/vEMan Why I started vEMan? Because I hate it to start my Windows VM to manage ESX(i) servers ;o) vEMan is (maybe) not needed if you use vCenter 5.x: http://kb.vmware.com/kb/2005377 --> vSphere >= v5 has a "web client" BUT keep in mind that there are... -
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SLOCCount is an easy-to-use tool that counts Source Lines of Code (SLOC). It auto-determines the language(s) (inc. C, C++, Ada, Assembly, shell, COBOL, C#, Fortran, Haskell, Java, LISP/Scheme, Perl, PHP, Python, Ruby, SQL). It also estimates cost & time.
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The sandbox libraries (libsandbox & pysandbox) are an open-source suite of software components for C/C++ and Python developers to create automated profiling tools and watchdog programs. The API's are designed for executing and instrumenting simple (single process) tasks, featuring policy-based behavioral auditing, resource quota, and statistics collecting. The sandbox libraries were originally designed and utilized as the core security module of a full-fledged online judge system for...
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Moihack Port-Flooder
A simple TCP/UDP Port Flooder written in Python.
This is a simple Port Flooder written in Python 3.2 Use this tool to quickly stress test your network devices and measure your router's or server's load. Features are available in features section below. Moihack DoS Attack Tool was the name of the 1st version of the program. Moihack Port-Flooder is the Reloaded Version of the program with major code rewrite and changes. Code is much smaller in size now - from about 130 pure lines of codes to 35 lines only. To run it you must... -
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Syrupy is a Python script that regularly takes snapshots of the memory and CPU load of one or more running processes, so as to dynamically build up a profile of their usage of system resources.
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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sarface is a user-interface to the sysstat/sar database which inputs data from sar and plots to a live X11 graph via gnuplot. It mimics the cmd-line options from sar but can cross-plot any two or more stats and apply simple mathematical functions them.
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Can emulate old computer on text the code pogram ideal to create kernel for operating system The begin the project the can emulate CPU(8080)and z80.
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Rugg is a hard drive and filesystem harness tool that allows you to test and benchmark drives and filesystems, by writing simple to complex scenarios that can mimic the behaviour of real-world applications.
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OpenLC is a set tools designed to facilitate benchmarking and stress testing of a wide variety of information servers (WEB, Email, FTP, LDAP, ...). A XML-RPC API is offered for developers interested in creating clients that query the services provid
