dimanzt Goto Github PK

.github

A set of SDKs for SmartNIC.

alexacode

A new skill to enable coding via Alexa

antrea

Kubernetes networking based on Open vSwitch

ark

A GPU-driven system framework for scalable AI applications

aws-virtual-gpu-device-plugin

AWS virtual gpu device plugin provides capability to use smaller virtual gpus for your machine learning inference workloads

azurepublicdataset

Microsoft Azure Traces

basemap

bnt

Bayes Net Toolbox for Matlab

bot-tester

OpenFaas lab5

cascadedfailuresinpower

cluster-data

Borg cluster traces from Google

complexnetwiki

ComplexNet team wiki

coursera-sdn

SDN Coursera Coursework

darknet

Convolutional Neural Networks

die

a paper template

dimanzt.com

Diman Zad Tootaghaj's Homepage

docker

My Docker scripts and Dockerfile for several frameworks.

etcd-1

Distributed reliable key-value store for the most critical data of a distributed system

faas

OpenFaaS - Serverless Functions Made Simple

faas-netes

Serverless Kubernetes with OpenFaaS (Functions as a Service)

fedml

FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. MLOps and App Marketplace are also enabled (https://open.fedml.ai).

game-theoretic-network-simulator

GTNS is a discrete-event network simulator targeted primarily for research and educational use. GTNS is written in Visual C++ programming language and supports different network topologies. This simulator was first produced to implement locally multipath adaptive routing (LMAR) protocol, classified as a new reactive distance vector routing protocol for MANETs. LMAR can find an ad-hoc path without selfish nodes and wormholes using an exhaustive search algorithm in polynomial time. Also when the primary path fails, it discovers an alternative safe path if network graph remains connected after eliminating selfish/malicious nodes. The key feature of LMAR to seek safe route free of selfish and malicious nodes in polynomial time is its searching algorithm and flooding stage that its generated traffic is equi-loaded compared to single-path routing protocols but its security efficiency to bypass the attacks is much better than the other multi-path routing protocols. LMAR concept is introduced to provide the security feature known as availability and a simulator has been developed to analyze its behavior in complex network environments [1]. Then we have added detection mechanism to the simulator, which can detect selfish nodes in network. The proposed algorithm is resilient against collision and can be used in networks which wireless nodes use directional antennas and it also defend against an attack that malicious nodes try to break communications by relaying the packets in a specific direction. Some game theoretic strategies to enforce cooperation in network have been implemented in GTNS, for example Forwarding-Ratio Strategy, TFT-Strategy and ERTFT. This tutorial helps new users to get familiar with GTNS and run different network scenarios.

ghc-scholarships

Comprehensive list of scholarships for the Grace Hopper Conference

hey

HTTP load generator, ApacheBench (ab) replacement

ibdump

in-network_ml

interdependentpowergrid

keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.

kube-bench

Checks whether Kubernetes is deployed according to security best practices as defined in the CIS Kubernetes Benchmark

kubernetesdatafabric

MapR Kubernetes Data Fabric