Global Sensitivity Analysis of a Gasoline Compression Ignition Engine Simulation with Multiple Targets on an IBM Blue Gene/Q Supercomputer

2016 ◽  
Author(s):  
Janardhan Kodavasal ◽  
Yuanjiang Pei ◽  
Kevin Harms ◽  
Stephen Ciatti ◽  
Al Wagner ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Compression Ignition ◽  
Compression Ignition Engine ◽  
Multiple Targets ◽  
Global Sensitivity ◽  
Engine Simulation ◽  
Blue Gene

Global Sensitivity Analysis of a Diesel Engine Simulation with Multi-Target Functions

2014 ◽  
Author(s):  
Yuanjiang Pei ◽  
Ruiqin Shan ◽  
Sibendu Som ◽  
Tianfeng Lu ◽  
Douglas Longman ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Diesel Engine ◽  
Global Sensitivity Analysis ◽  
Global Sensitivity ◽  
Engine Simulation

Development of a Stiffness-Based Chemistry Load Balancing Scheme, and Optimization of I/O and Communication, to Enable Massively Parallel High-Fidelity Internal Combustion Engine Simulations

2015 ◽  
Author(s):  
Janardhan Kodavasal ◽  
Kevin Harms ◽  
Priyesh Srivastava ◽  
Sibendu Som ◽  
Shaoping Quan ◽  
...  
Keyword(s):  
Load Balancing ◽  
Combustion Engine ◽  
Mesh Size ◽  
Test Case ◽  
Compression Ignition ◽  
Compression Ignition Engine ◽  
Engine Simulation ◽  
Output Performance ◽  
Crank Angle ◽  
Blue Gene

A closed-cycle gasoline compression ignition engine simulation near top dead center (TDC) was used to profile the performance of a parallel commercial engine computational fluid dynamics code, as it was scaled on up to 4096 cores of an IBM Blue Gene/Q supercomputer. The test case has 9 million cells near TDC, with a fixed mesh size of 0.15 mm, and was run on configurations ranging from 128 to 4096 cores. Profiling was done for a small duration of 0.11 crank angle degrees near TDC during ignition. Optimization of input/output performance resulted in a significant speedup in reading restart files, and in an over 100-times speedup in writing restart files and files for post-processing. Improvements to communication resulted in a 1400-times speedup in the mesh load balancing operation during initialization, on 4096 cores. An improved, “stiffness-based” algorithm for load balancing chemical kinetics calculations was developed, which results in an over 3-times faster run-time near ignition on 4096 cores relative to the original load balancing scheme. With this improvement to load balancing, the code achieves over 78% scaling efficiency on 2048 cores, and over 65% scaling efficiency on 4096 cores, relative to 256 cores.

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