48 citations · 140 across the 31 of their papers we have counts for
36 papers
Hybrid Edge-HPC Systems for Low-Latency Data-Driven Inference
Liubov Kurafeeva, Ryan Hartung, Benjamin Carter +9
Emerging cyber-physical systems increasingly require low-latency inference from streaming sensor data while maintaining models that reflect complex and evolving physical processes.…
RHAPSODY: Execution of Hybrid AI-HPC Workflows at Scale
Aymen Alsaadi, Mason Hooten, Mariya Goliyad +14
Hybrid AI-HPC workflows combine large-scale simulation, training, high-throughput inference, and tightly coupled, agent-driven control within a single execution campaign. These wor…
Adaptive Protein Design Protocols and Middleware
Aymen Alsaadi, Jonathan Ash, Mikhail Titov +4
Computational protein design is experiencing a transformation driven by AI/ML. However, the range of potential protein sequences and structures is astronomically vast, even for mod…
Integrating and Characterizing HPC Task Runtime Systems for hybrid AI-HPC workloads
Andre Merzky, Mikhail Titov, Matteo Turilli +1
Scientific workflows increasingly involve both HPC and machine-learning tasks, combining MPI-based simulations, training, and inference in a single execution. Launchers such as Slu…
xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture
Liubov Kurafeeva, Alan Subedi, Ryan Hartung +9
Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemp…
Scalable Runtime Architecture for Data-driven, Hybrid HPC and ML Workflow Applications
Andre Merzky, Mikhail Titov, Matteo Turilli +3
Hybrid workflows combining traditional HPC and novel ML methodologies are transforming scientific computing. This paper presents the architecture and implementation of a scalable r…
Exascale Workflow Applications and Middleware: An ExaWorks Retrospective
Aymen Alsaadi, Mihael Hategan-Marandiuc, Ketan Maheshwari +9
Exascale computers offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discover…
ExaWorks Software Development Kit: A Robust and Scalable Collection of Interoperable Workflow Technologies
Matteo Turilli, Mihael Hategan-Marandiuc, Mikhail Titov +13
Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different typ…
Design and Implementation of an Analysis Pipeline for Heterogeneous Data
Arup Kumar Sarker, Aymen Alsaadi, Niranda Perera +8
Managing and preparing complex data for deep learning, a prevalent approach in large-scale data science can be challenging. Data transfer for model training also presents difficult…
Workflow Mini-Apps: Portable, Scalable, Tunable & Faithful Representations of Scientific Workflows
Ozgur Ozan Kilic, Tianle Wang, Matteo Turilli +4
Workflows are critical for scientific discovery. However, the sophistication, heterogeneity, and scale of workflows make building, testing, and optimizing them increasingly challen…
PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs
Mihael Hategan-Marandiuc, Andre Merzky, Nicholson Collier +10
It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective…
RAPTOR: Ravenous Throughput Computing
Andre Merzky, Matteo Turilli, Shantenu Jha
We describe the design, implementation and performance of the RADICAL-Pilot task overlay (RAPTOR). RAPTOR enables the execution of heterogeneous tasks -- i.e., functions and execut…
Pipeline for Automating Compliance-based Elimination and Extension (PACE2): A Systematic Framework for High-throughput Biomolecular Material Simulation Workflows
Srinivas C. Mushnoori, Ethan Zang, Akash Banerjee +5
The formation of biomolecular materials via dynamical interfacial processes such as self-assembly and fusion, for diverse compositions and external conditions, can be efficiently p…
A Scalable Solution for Running Ensemble Simulations for Photovoltaic Energy
Weiming Hu, Guido Cervone, Matteo Turilli +2
This chapter proposes and provides an in-depth discussion of a scalable solution for running ensemble simulation for solar energy production. Generating a forecast ensemble is comp…
ExaWorks: Workflows for Exascale
Aymen Al-Saadi, Dong H. Ahn, Yadu Babuji +12
Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific dis…
Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening
Austin Clyde, Thomas Brettin, Alexander Partin +8
We propose a benchmark to study surrogate model accuracy for protein-ligand docking. We share a dataset consisting of 200 million 3D complex structures and 2D structure scores acro…
Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +55
Scientific workflows are a cornerstone of modern scientific computing, and they have underpinned some of the most significant discoveries of the last decade. Many of these workflow…
RADICAL-Pilot and Parsl: Executing Heterogeneous Workflows on HPC Platforms
Aymen Alsaadi, Logan Ward, Andre Merzky +4
Workflows applications are becoming increasingly important to support scientific discovery. That is leading to a proliferation of workflow management systems and, thus, to a fragme…
Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers
Agastya P. Bhati, Shunzhou Wan, Dario Alfè +26
The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottle…
Design and Performance Characterization of RADICAL-Pilot on Leadership-class Platforms
Andre Merzky, Matteo Turilli, Mikhail Titov +2
Many extreme scale scientific applications have workloads comprised of a large number of individual high-performance tasks. The Pilot abstraction decouples workload specification,…
Scalable HPC and AI Infrastructure for COVID-19 Therapeutics
Hyungro Lee, Andre Merzky, Li Tan +15
COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE re…
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
Aymen Al Saadi, Dario Alfe, Yadu Babuji +33
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive…
Characterizing the Performance of Executing Many-tasks on Summit
Matteo Turilli, Andre Merzky, Thomas Naughton +2
Many scientific workloads are comprised of many tasks, where each task is an independent simulation or analysis of data. The execution of millions of tasks on heterogeneous HPC pla…
RADICAL-Cybertools: Middleware Building Blocks for Scalable Science
Vivek Balasubramanian, Shantenu Jha, Andre Merzky +1
RADICAL-Cybertools (RCT) are a set of software systems that serve as middleware to develop efficient and effective tools for scientific computing. Specifically, RCT enable executin…