CloneX

Cloned eXecution of simulations is a powerful decision-making system to incrementally evaluate millions of what-if scenarios and scale to 1000s of GPUs.

Overview

CloneX is a novel system we designed for scalable simulation cloning, consisting of a conceptual simulation framework, algorithmic foundations, and a highly scalable runtime interface. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a large parallel system without full physical duplication of computation and memory.

CloneX efficiently simulates a tree of multiple what-if scenarios unraveled during the course of a normal (base) simulation. Cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree.

CloneX has been tested on 1000s of GPUs of a supercomputing system and evaluated with multiple benchmarks – such as heat diffusion, forest fire, and disease propagation models – delivering a speed up of over two orders of magnitude compared to replicated runs.

CloneX represents a major leap in ensemble simulations as a significantly faster and scalable way to execute many what-if scenarios of large simulations.

Organization

• Sponsors: US Department of Energy (DOE)
  • Office: Advanced Scientific Computing Research (ASCR)
    • Program: Early Career Research Program (ECRP)
  • Office: ORNL Strategic Planning Office
    • Program: Laboratory-Directed Research and Develoopment (LDRD)
• Period: 2015-2017

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Related Publications

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs: Fast What–If Analyses of Localized and Dynamic Effects

A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

Kalyan Perumalla, Maksudul Alam

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Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. We present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning.

Srikanth Yoginath, Kalyan Perumalla

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