Search Results for "data center simulator"

composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. ...

Bionic is an on-premise generative AI platform positioned as a private replacement for ChatGPT, with a strong emphasis on data confidentiality, team collaboration, and enterprise deployment. It can run locally on a laptop for small pilots, but it is also designed to scale into data center and Kubernetes environments for much larger usage. The interface is intentionally familiar, offering a ChatGPT-like experience with customizable branding, fast Rust-based performance, and conversation history management. ...

NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated...

The DLP tool was ideated and developed by: Dr. Luca Mazzola, MsC. Patrick Kapahnke, and PD Dr. Matthias Klusch at the German Research Center for Artificial Intelligence DFKI GmbH (http://www.dfki.de ) in Saarbrücken, Germany. Copyright: DFKI, 2017, licence GLP see https://www.gnu.org/licenses/gpl-3.0.en.html For bug reports, technical problems and feature requests please contact: Luca Mazzola: luca.mazzola@dfki.de or mazzola.luca@gmail.com Patrick Kapahnke: patrick.kapahnke@dfki.de

Siafu simulates individual agents and their context, from home to city-wide scenarios. As a developer, you use the API to write your simulation for the purposes of data-set generation, test or visualization, optionally hooking it to your own application.

An easy to extend, highly graphical, easy to use 2D robot simulator specialized for path planning algorithms. Can be used in testing various robotic algorithms, and already used for comparison of path planning algorithms like RRT, RRTConnect, PRM, RboT..

This project simulates a multi-agent system (swarm) behavior both graphically and not. The purpose of this project is to research the properties suggested in "stability analysis of swarms" V.Gazi & K.M.Passino. Using the vpython library for 3D modeling

A feedback-enhanced framework for routing in wireless sensor networks. Speeds up the process of implementing routing techniques. Enables piggybacking of routing information on data packets. Written for the Omnet++ simulator and the Mobility Framework.

Diagram (JGraph) driven simulator. Bondgraphs > nonlinear differantial system > plot: implemented for economics and ecology. Network analysis: emergy propagation implemented. Would also fit for electronics, mechanics, cost, GWP, footprint analysis.

The Macro Agent Transport Event-based Simulator (MATES) is intended to efficiently investigate the behavior of distributed agent based systems over mobile ad hoc networks (MANETs). MATES provides an expandable environment for agent-based system testing.

OpenSim - Open Simulator. Primarily a 3D simulator for multiple indoor and outdoor mobile robots. Includes 3D real-time rendering (via OSG) and a physics engine (via ODE). Current emphasis is on manipulators.

Fungus is a framework for distributed simulation by multi-agents. It uses a very modular architecture. A GUI is provided. In our model, everything is Agent. Even the environnement. You have an access to the communication's 'canals'.