On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective

We implement and benchmark parallel I/O methods for the fully-manycore driven particle-in-cell code PIConGPU. Identifying throughput and overall I/O size as a major challenge for applications on today's and future HPC systems, we present a scaling law characterizing performance bottlenecks in state-of-the-art approaches for data reduction. Consequently, we propose, implement and verify multi-threaded data-transformations for the I/O library ADIOS as a feasible way to trade underutilized host-side compute potential on heterogeneous systems for reduced I/O latency.Comment: 15 pages, 5 figures, accepted for DRBSD-1 in conjunction with ISC'1

EDACs and test integration strategies for NAND flash memories

Mission-critical applications usually presents several critical issues: the required level of dependability of the whole mission always implies to address different and contrasting dimensions and to evaluate the tradeoffs among them. A mass-memory device is always needed in all mission-critical applications: NAND flash-memories could be used for this goal. Error Detection And Correction (EDAC) techniques are needed to improve dependability of flash-memory devices. However also testing strategies need to be explored in order to provide highly dependable systems. Integrating these two main aspects results in providing a fault-tolerant mass-memory device, but no systematic approach has so far been proposed to consider them as a whole. As a consequence a novel strategy integrating a particular code-based design environment with newly selected testing strategies is presented in this pape