Abstract: Understanding the performance of program execution is essential when optimizing simulations run on high-performance supercomputers. Instrumenting and profiling codes is itself a difficult task and interpreting the resulting complex data is often facilitated through visualization of the gathered measures. However, these measures typically ignore spatial information specific to a simulation, which may contain useful knowledge on program behavior. Linking the instrumentation data to the visualization of performance within a spatial context is not ...
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Topics: 
Data science
Data mining