TADSim: Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

Journal Article · Thu Apr 16 00:00:00 EDT 2015 · ACM Transactions on Modeling and Computer Simulation

DOI:https://doi.org/10.1145/2699715· OSTI ID:1329851

Mniszewski, Susan M. ^[1]; Junghans, Christoph ^[1]; Voter, Arthur F. ^[1]; Perez, Danny ^[1]; Eidenbenz, Stephan J. ^[1]

---

1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. Here, we present a new class of tools called application simulators—parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation. Parameterized choices for the algorithmic method and hardware options provide a rich space for design exploration and allow us to quickly find well-performing software--hardware combinations. We demonstrate our approach with a TADSim simulator that models the temperature-accelerated dynamics (TAD) method, an algorithmically complex and parameter-rich member of the accelerated molecular dynamics (AMD) family of molecular dynamics methods. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We accomplish this by identifying the time-intensive elements, quantifying algorithm steps in terms of those elements, abstracting them out, and replacing them by the passage of time. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We extend TADSim to model algorithm extensions, such as speculative spawning of the compute-bound stages, and predict performance improvements without having to implement such a method. Validation against the actual TAD code shows close agreement for the evolution of an example physical system, a silver surface. Finally, focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights and suggested extensions.

• Research Organization: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: LDRD; USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC52-06NA25396
• OSTI ID: 1329851
• Report Number(s): LA-UR--13-28342
• Journal Information: ACM Transactions on Modeling and Computer Simulation, Journal Name: ACM Transactions on Modeling and Computer Simulation Journal Issue: 3 Vol. 25; ISSN 1049-3301
• Publisher: Association for Computing Machinery
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
Computer Science
Material Science
temperature-accelerated dynamics (TAD) method