Search Results for "network performance" - Page 4
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Showing 106 open source projects for "network performance"
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Mixup-CIFAR10
mixup: Beyond Empirical Risk Minimization
mixup-cifar10 is the official PyTorch implementation of “mixup: Beyond Empirical Risk Minimization” (Zhang et al., ICLR 2018), a foundational paper introducing mixup, a simple yet powerful data augmentation technique for training deep neural networks. The core idea of mixup is to generate synthetic training examples by taking convex combinations of pairs of input samples and their labels. By interpolating both data and labels, the model learns smoother decision boundaries and becomes more... -
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DIGITS
Deep Learning GPU training system
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. ... -
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Toapi
Convert websites into structured APIs automatically with Python tool
...Developers define items and routes that determine how web pages are parsed and how the resulting data is exposed through the API interface. It also includes mechanisms for caching both page content and API requests, helping reduce repeated network calls and improving performance. Because the generated service is built on top of a Flask application, it can be deployed like any other Flask-based project and integrated into existing Python workflows. -
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Pyben-nio
Simple python network benchmark that you can ride on!
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gain
Asyncio-based Python framework for building fast web crawling spiders
Gain is a Python web crawling framework designed to simplify the process of building efficient and scalable web scrapers. It is built on top of asynchronous technologies such as asyncio, aiohttp, and uvloop to support high-performance crawling with concurrent network requests. It provides a structured framework for creating spiders that can navigate websites, extract structured data, and process the collected results. Developers define crawlers using components such as spiders, parsers, and items, allowing them to organize crawling logic and data extraction rules clearly. ... -
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TEACUP
TCP Experiment Automation Controlled Using Python
TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. -
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Pulsar framework
Event driven concurrent framework for Python
Event-driven concurrent framework for Python. Pulsar's goal is to provide an easy way to build scalable network programs. In the Hello world! webserver example above, many client connections can be handled concurrently. Pulsar tells the operating system (through epoll or select) that it should be notified when a new connection is made, and then it goes to sleep. Pulsar uses the asyncio module from the standard python library and it can be configured to run in multi-processing mode. The http... -
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EDCC-CNG
Exploration and categorization of CREs and CRMs
...We developed two programs that serve as exploratory tools in the analysis of CRM-mediated control of gene expression: “Exploration of Distinctive CREs and CRMs” (EDCC) and “CRM Network Generator” (CNG). EDCC correlates the presence and positions of CREs/CRMs with gene expression data and identifies candidate regulatory elements for further functional analysis. CNG provides an unbiased neural network approach to assess the importance of positional features that were determined by EDCC. To sustain a high computational performance even for large datasets, the mostly in Python 3 written programs use k-mer based indexing, parallelization and a neural network approach for categorization. ... -
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asyncoro
Python framework for asynchronous, concurrent, distributed programming
asyncoro is a Python framework for developing concurrent, distributed, network programs with asynchronous completions and coroutines. Asynchronous completions implemented in asyncoro are sockets (non-blocking sockets), database cursors, sleep timers and locking primitives. Programs developed with asyncoro have same logic and structure as Python programs with threads, except for a few syntactic changes. asyncoro supports socket I/O notification mechanisms epoll, kqueue, /dev/poll (and poll and select, where necessary), and Windows I/O Completion Ports (IOCP) for high performance and scalability, and SSL for security -
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mod_openopc
just plain WORKS
mod_openopc is a full featured implementation of the OpenOPC library for Python. It is cross platform compatible (full Python 2.5 and up). We used to recommend running it on a POSIX platform (Unix / Linux), but thanks to modest efforts since 2014, performance in Windows OS environments is excellent. -
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Ganglia
Scalable, distributed monitoring system for high-performance computing
Ganglia is a scalable distributed monitoring system for high-performance computing systems such as clusters and Grids. It is based on a hierarchical design targeted at federations of clusters. Supports clusters up to 2000 nodes in size. -
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netmonsql
Network performance monitoring and logging script for Cisco devices.
NetMon_Cisco_to_SQL.py is a basic network performance monitoring and logging script for Cisco devices. It gathers parameters (CPU Utilization, Used Processor Memory, Used IO Memory, UP Ethernet Interfaces density, in percent velues) from Cisco routers by parsing command outputs and exports them to a MySQL database. NetMon_Query.py is a query script for the MySQL database in the form of an interactive menu for generating statistics. -
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DataCopy For SQLServer
Data Copy tool for SQL Server and Oracle
Migrate your data from SQLServer to Oracle without creating single dump file. Input is a SQLServer query file defining dataset you want to copy to Oracle. Target table has to exist for copy to go through. Turbo mode offers 5x copy performance improvement. -
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Data Spooler for SQLServer #SaveUkraine
Extracts table or query data from SQL Server 2005, 2008, 2012
#SaveUkraine #StopRussia #FreeUkraine #StopPutin #CrimeaIsUkraine #UnitedForUkraine #RussiaInvadedUkraine Spools/extracts/dump table or query data from SQL Server 2015, 2008,2012. Serial spool creates single dump file. Turbo mode offers 5x spool performance improvement. Sharded turbo more creates multiple files. -
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Debian Unstable/testing alpha.
Pre-Alpha Console distro for high performance Linux computing.
Basic Debian INTEL/AMD HPC console/desktop multi purpose. Linux for software devs/QA and thin laboratory clusters. MIC hardware, NUMA and live network memory and full IPv6 are supported. Final alpha release features: ======== * Usb image * General debian repos * VM optimizations * Hugepages by default * CGROUPs optimized by default * ALSA * Latest Debugging / Baremetal kernels * Full Haswell and MIC support in test * Full optimized python support * Full... -
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AMBIENT
Find active modules in metabolic networks using high-throughput data
...If you wish to use the version used in the paper it is v0.6.3, however I recommend using the latest version which works in the same way but with additional options and has stability and performance improvements. Thanks for your interest! AMBIENT (Active Modules for Bipartite Networks) is a Python module that uses simulated annealing to find areas of a metabolic network (modules) that have some consistent characteristic. AMBIENT does not require predefined pathways and gives highly specific predictions of affected areas of metabolism. ... -
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minder
Monitoring your infrastructure for free.
This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else? Status: PreAlpha, so... -
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BCMSlib is a web user interface software that monitors the status and performance of a call center. It uses data collected in the Basic Call Management System (BCMS) on a Avaya DEFINITY System or a S8300/S8400/S8500/S8700 system.
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A high-performance extensible simulation framework for network coding protocols, written in Python.
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XRay is an analysis tool built upon your SCMs, aimed to consolidade project statistics from many repositories in a single tool, generating code reports and development statistics obtained from log data and file versions.
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A Web based P2P model that delivers high performance P2P computing over network through a web based UI.
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NetWhistler is SNMP monitoring software that offers integrated fault and performance management functionality. This Java program auto-detects networks and presents them on graphical maps, which reflect host status. Mila NNM is a pyQT fork of Netwhistler.
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The goals of the project are to empower the Nagios community with Enterprise Performance Monitoring plugins for COTS Applications[Oracle - DB2 - MSSQL - PostgreSQL - Ingres - Weblogic - WebSphere - Jboss - Apache - IIS - DotNet - Documentum - etc] .
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PGGT (Performance Gathering and Graphing Tools) is a set of tools for gathering and graphing the information collected by the *stat suite of commands: iostat, vmstat, netstat.
