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<strong>RADICAL-Pilot</strong> (RP) is a scalable and flexible Pilot-Job system that provides application-level resource management capabilities on HPC resources. RP interfaces to various low level resource managers like Slurm, PBS(Pro), and also to various task execution backends like Slurm, OpenMPI, MPICH, PRRTE, JSRUN, Flux, Dragon, and others.
<strong>RADICAL-AsyncFlow</strong> (RAF) is an asynchronous scripting library for building high-performance, scalable workflows that run on HPC systems, clusters, and local machines. Designed for flexibility and speed, it allows users to compose complex workflows from async and sync tasks with clear dependencies, while ensuring efficient execution at any scale with different execution backends.
<strong>ROSE</strong>: RADICAL Orchestrator for Surrogate Exploration is a Python framework designed for concurrent and adaptive execution of ML learning workflows on high-performance computing (HPC) resources. It empowers scientists and engineers to develop active learning (AL) and reinforcement learning (RL) via a pre-defined Learning Policies for scientific discovery.
<strong>IMPRESS</strong>: Integrated Machine-learning for PRotEin Structures at Scale is a high-performance computational framework designed to enable the inverse design of proteins using advanced foundation models such as AlphaFold and ESM2. It leverages a closed-loop design process that integrates structure prediction, sequence optimization, and machine learning-based analysis.
<strong>DeepDriveMD</strong>: Deep-Learning Driven Adaptive Molecular Simulations (DDMD) is a Python framework for orchestrating AI-steered molecular dynamics (MD) simulations on HPC systems. The next generation of DDMD is built on ROSE, it enables concurrent ensembles of MD simulations and AI model training.
The <strong>Workflow MiniApp</strong> framework provides the environment to build compact, self-contained applications that emulate key aspects of larger scientific workflows, enabling researchers to explore, test, and optimize computational tasks without running the full-scale workflow. At the core is wfMiniAPI, an open-source Python and C++ library.
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