{"repo":"CrayLabs/SmartSim","free":true,"listed":false,"github":"https://github.com/CrayLabs/SmartSim","clone":"git clone https://github.com/CrayLabs/SmartSim.git","description":"SmartSim Infrastructure Library.","language":"Python","stars":275,"topics":["hpc","machine-learning","simulation","workflow"],"license":"BSD-2-Clause","category":"machine-learning","readme_excerpt":"Home     Install     Documentation     Cray Labs     Contact     Join us on Slack!     ------------ SmartSim SmartSim is made up of two parts 1. SmartSim Infrastructure Library (This repository) 2. SmartRedis The two library components are designed to work together, but can also be used independently. SmartSim is a workflow library that makes it easier to use common Machine Learning (ML) libraries, like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and applications. SmartSim launches ML infrastructure on HPC systems alongside user workloads. SmartRedis provides an API to connect HPC workloads, particularly (MPI + X) simulations, to the ML infrastructure, namely the The Orchestrator database, launched by SmartSim. Applications integrated with the SmartRedis clients, written in Fortran, C, C++ and Python, can send data to and remotely request SmartSim infrastructure to execute ML models and scripts on GPU or CPU. The distributed Client-Server paradigm allows for data to be seamlessly exchanged between applications at runtime without the utilization of MPI. ---------- Table of Contents - SmartSim - Quick Start - SmartSim Infrastructure Library - Experiments - Hello World - Hello World MPI - Experiments on HPC Systems - Interactive Launch Example - Batch Launch Examples - Infrastructure Library Applications - Redis + RedisAI - Local Launch - Interactive Launch - Bat","default_branch":null,"files":null,"tree":[],"storefront":"/r/CrayLabs","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/CrayLabs/SmartSim/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}