PERI is a SciDAC Institute focused on delivering petascale performance to complex scientific applications running on Leadership Class computing systems. This website highlights the tools and publications produced by the PERI project. Most of the ongoing work and discussion can be found on the PERI wiki

As we look to the future, achieving good performance on high-end computing (HEC) systems is growing ever more challenging due to enormous scale, increasing architectural complexity, and increasing application complexity. To address these challenges, the SciDAC-3 the Performance Engineering Research Institute for Enabling Technology (PERI) is pursuing a unified, tripartite research plan encompassing:

  1. Performance modeling and prediction
  2. Automatic performance optimization
  3. Performance engineering of high profile applications

The PERI performance modeling and prediction activity will develop and refine our performance models, significantly reducing the cost of collecting the data upon which the models are based and increasing model fidelity, speed and spurred by the strong user preference for automatic tools. This work is building on previous successful activities such as ATLAS, which has automatically tuned components of the LAPACK linear algebra library, the highly successful FFTW library, and other recent work. In our third major component, application engagement, we directly interact with SciDAC applications, including "tiger teams" that focus on particular codes.