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Performance and Scaling Effects of MD Simulations using NAMD 2.7 and 2.8

Performance and Scaling Effects of MD Simulations using NAMD 2.7 and 2.8. GradOS Course Project Progress Report Kevin Kastner Xueheng Hu. Introduction. Molecular Dynamics (MD) MD is extremely computationally intensive Primarily due to the sheer size of the system

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Performance and Scaling Effects of MD Simulations using NAMD 2.7 and 2.8

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  1. Performance and Scaling Effects of MD Simulations using NAMD 2.7 and 2.8 GradOS Course Project Progress Report Kevin Kastner Xueheng Hu

  2. Introduction • Molecular Dynamics (MD) • MD is extremely computationally intensive • Primarily due to the sheer size of the system • Large system simulation can potentially take thousands of years on a modern desktop • NAMD – Parallelized simulation tool for MD • Recent release is 2.8

  3. GPCR Simulation Example

  4. (Original) Proposed Work • Performance Comparison: NAMD 2.7 vs 2.8 • Investigate the main cause of performance decrease of NAMD 2.8 • Will test same protein system using each version, comparing efficiency of each • How different size/complexity of the system affects the performance of NAMD • Scalability observation • Determine max performance

  5. Preliminary Testing • G-Protein Coupled Receptor (GPCR) simulation system contains ~57000 atoms • Testing simulation efficiency with varying core amounts • 12, 24, 48, 96, 120, 196 • 300, 504, 1008 • 5 runs done per core set for each version

  6. Preliminary Results

  7. Preliminary Results

  8. Future Work • The Scaling Observation How different sizes/complexity of system affect the performance of NAMD • Further investigation of performance diff. between NAMD2.7b1 and NAMD2.8 • Capture the system and network information • Strace, NetHogs

  9. Questions?

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