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Knüpfer, Andreas

Publications and source records attributed to Knüpfer, Andreas.

Enabling event tracing at leadership-class scale through I/O forwarding middleware. In: HPDC '12 Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing

Event tracing is an important tool for understanding the performance of parallel applications. As concurrency increases in leadership-class computing systems, the quantity of performance log data can overload the parallel file system, perturbing the application being observed. In this work we present a solution for event tracing at leadership scales. We enhance the I/O forwarding system software to aggregate and reorganize log data prior to writing to the storage system, significantly reducing the burden on the underlying file system for this type of traffic. Furthermore, we augment the I/O forwarding system with a write buffering capability to limit the impact of artificial perturbations from log data accesses on traced applications. To validate the approach, we modify the Vampir tracing toolset to take advantage of this new capability and show that the approach increases the maximum traced application size by a factor of 5x to more than 200,000 processes.

Ilsche, Thomas↗

Trace-based performance analysis for the petascale simulation code FLASH

Performance analysis of applications on modern high-end petascale systems is increasingly challenging due to the rising complexity and quantity of the computing units. This paper presents a performance-analysis study using the Vampir performance-analysis tool suite, which examines application behavior as well as the fundamental system properties. This study was carried out on the Jaguar system at Oak Ridge National Laboratory, the fastest computer on the November 2009 Top500 list. We analyzed the FLASH simulation code that is designed to be scaled with tens of thousands of CPU cores, which means that using existing performance-analysis tools is very complex. The study reveals two classes of performance problems that are relevant for very high CPU counts: MPI communication and scalable I/O. For both, solutions are presented and verified. Finally, the paper proposes improvements and extensions for event tracing tools in order to allow scalability of the tools towards higher degrees of parallelism.

Computer Science↗