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This paper discusses the use of software cache partitioning techniques to study and improve cache behavior of HPC applications. Most existing studies use this partitioning to solve quality of service issues, like fair distribution of a shared cache among running processes. We believe that, in the HPC context of a single application being studied/optimized on the system, with a single thread per core, cache partitioning can be used in new and interesting ways. First, we propose an implementation of software cache partitioning using the well known page coloring technique. This implementation differs from existing ones by giving control of the partitioning to the application programmer. Developed on the most popular OS in HPC (Linux), this cache control scheme has low overhead both in memory and CPU while being simple to use. Second, we illustrate how this user-controlled cache partitioning can lead to efficient measurements of cache behavior of a parallel scientific visualization application. While current tools require expensive binary instrumentation of an application to obtain its working sets, our method only needs a few unmodified runs on the target platform. Finally, we discuss the use of our scheme to optimize memory intensive applications by isolating each of their critical data structures into dedicated cache partitions. This isolation allows the analysis of each structure cache requirements and leads to new and significant optimization strategies. To the best of our knowledge, no other existing tool enables such tuning of HPC applications.