Author Description

Over the last decades an incredible amount of resources has been devoted to building ever more powerful supercomputers However, exploiting the full capabilities of these machines is becoming exponentially more difficult with each new generation of hardware To help understand and optimize the behavior of massively parallel simulations the performance analysis community has created a wide range of tools and APIs to collect performance data, such as flop counts, network traffic or cache behavior at the largest scale However, this success has created a new challenge, as the resulting data is far too large and too complex to be analyzed in a straightforward manner Therefore, new automatic analysis approaches must be developed to allow application developers to intuitively understand the multiple, interdependent effects that their algorithmic choices have on the final performance This workshop will bring together researchers and practitioners from the areas of performance analysis, ap