MOFA couples a fine-tuned diffusion model with LAMMPS, CP2K, and RASPA simulations in an online learning loop to generate stable MOFs with high CO2 adsorption, demonstrating near-linear scaling on up to 450 nodes.
Object Proxy Patterns for Accelerating Distributed Applications
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves optimization to the application programmer -- optimization that becomes more difficult as data become larger. The transparent object proxy, which provides wide-area references that can resolve to data regardless of location, has been demonstrated as an effective low-level building block in such situations. Here we propose three high-level proxy-based programming patterns -- distributed futures, streaming, and ownership -- that make the power of the proxy pattern usable for more complex and dynamic distributed program structures. We motivate these patterns via careful review of application requirements and describe implementations of each pattern. We evaluate our implementations through a suite of benchmarks and by applying them in three substantial scientific applications, in which we demonstrate substantial improvements in runtime, throughput, and memory usage.
citation-role summary
citation-polarity summary
fields
cs.DC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
MOFA: Discovering Materials for Carbon Capture with a GenAI- and Simulation-Based Workflow
MOFA couples a fine-tuned diffusion model with LAMMPS, CP2K, and RASPA simulations in an online learning loop to generate stable MOFs with high CO2 adsorption, demonstrating near-linear scaling on up to 450 nodes.