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Abstract. The paper presents methods for instrumentation and measurement of applications' memory allocation behavior over time. It provides some background about possible performance problems related to memory allocation as well as to memory allocator libraries. Then, different methods for data acquisition and representation are discussed. Finally, memory allocation tracing integrated in VampirTrace is demonstrated with a real-world HPC example application from aerodynamical simulation and optimization.

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 with the Vampir performance analysis tool suite that examines the application behavior as well as the fundamental system properties.The study is done on the ORNL's Cray XT4 system Jaguar consisting of more than 30,000 CPU cores. We analyze the FLASH simulation code that is designed to scale towards tens of thousands of CPU cores. This situation makes it very complex to apply existing performance analysis tools. Yet, the study reveals two classes of performance problems that become relevant with 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.

This paper describes Indiana University's implementation, performance testing, and use of a large high performance computing system. IU's Big Red, a 20.48 TFLOPS IBM e1350 BladeCenter cluster, appeared in the 27th Top500 list as the 23rd fastest supercomputer in the world in June 2006. In spring 2007, this computer was upgraded to 30.72 TFLOPS. The e1350 BladeCenter architecture, including two internal networks accessible to users and user applications and two networks used exclusively for system management, has enabled the system to provide good scalability on many important applications while being well manageable. Implementing a system based on the JS21 Blade and PowerPC 970MP processor within the US TeraGrid presented certain challenges, given that Intel‐compatible processors dominate the TeraGrid. However, the particular characteristics of the PowerPC have enabled it to be highly popular among certain application communities, particularly users of molecular dynamics and weather forecasting codes. A critical aspect of Big Red's implementation has been a focus on Science Gateways, which provide graphical interfaces to systems supporting end‐to‐end scientific workflows. Several Science Gateways have been implemented that access Big Red as a computational resource—some via the TeraGrid, some not affiliated with the TeraGrid. In summary, Big Red has been successfully integrated with the TeraGrid, and is used by many researchers locally at IU via grids and Science Gateways. It has been a success in terms of enabling scientific discoveries at IU and, via the TeraGrid, across the US. Copyright © 2009 John Wiley & Sons, Ltd.

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