In the last ten years, computing capability has increased many-fold, and correspondingly data volumes have grown by an even larger amount. Many traditional application domains have now become data intensive. It is estimated that organizations with high-performance computing infrastructures and data centers are doubling the amount of data that they are archiving every year. Recent advances in computing architectures require that middleware and application software be re-engineered to fully exploit heterogeneous resources, memory hierarchies, and I/O pipelines. Cloud computing has become a practical and cost effective solution for providers and consumers, ranging from business analytics to scientific computing. The utility of cloud computing has been shown to provide significant benefits in data mining, machine learning and knowledge discovery. Cloud computing also has great potential to revolutionize extreme scale data analytics; but there are many obstacles which must be overcome to gain wide spread adoption. The integration of HPC and cloud infrastructure, for example, must be addressed in a manner that is both usable and scalable. This workshop intends to bring together members of academia, government and industry to discuss new and emerging trends in computing architectures, programming models, I/O services, and data analytics. This workshop will also identify the greatest challenges in embracing high-end computing infrastructure for scaling I/O and algorithms to extreme scale datasets. We invite researchers, developers, and users to participate in this workshop to share, contribute, and discuss the emerging challenges in developing knowledge discovery solutions and frameworks targeting modern computing platforms.