Tell me, I'll forget, Show me, I may remember, Involve me, I'll understand." -Confucius This proverb describes the essence of our paper and the motivation behind the development of the Interactive Parallelization Tool (IPT) that can transform serial applications into multiple parallel variants. The end-users of IPT must have an understanding of the basic concepts involved in parallel programming (e.g., data distribution and data gathering). After developing an understanding of the basic parallel programming concepts, IPT can be used by its target audience (domain-experts and students) to semi-automatically generate parallel programs using multiple parallel programming paradigms (MPI, OpenMP, and CUDA), and learn about these paradigms through observation and comparison. This IPT-based personalized learning approach complements the traditional methods of learning and training that usually emphasize the syntax and semantics of one or more programming standards. The main benefit of IPT is that it provides a jumpstart to the domain-experts in using modern HPC platforms for their research and development needs, and hence lowers the adoption barriers to HPC.

No abstract

In this chapter the essential aspects of anesthesia for epiglottitis are reviewed. Subtopics include defining the classic chest X-ray signs in patients with this disease, such as the thumb print sign, airway management, and steps to take to avoid laryngospasm in these patients. The case presented is a pediatric patient with emergent respiratory distress. The chapter is divided into preoperative, intraoperative, and postoperative sections with important subtopics related to the main topic in each section. Issues addressed for preoperative evaluation include diagnosis in this patient, volume status, and selection of anesthetic technique. Intraoperative topics focus on airway management. Postoperative management addresses primarily extubation.

Heterogeneous architectures can improve the performance of applications with computationally intensive, data-parallel operations. Even when these architectures may reduce the execution time of applications, there are opportunities for additional performance improvement as the memory hierarchy of the central processor cores and the graphics processor cores are separate. Applications executing on heterogeneous architectures must allocate space in the GPU global memory, copy input data, invoke kernels, and copy results to the CPU memory. This scheme does not overlap inter-memory data transfers and GPU computations, thus increasing application execution time. This research presents a software architecture with a runtime pipeline system for GPU input/output scheduling that acts as a bidirectional interface between the GPU computing application and the physical device. The main aim of this system is to reduce the impact of the processor-memory performance gap by exploiting device I/O and computation overlap. Evaluation using application benchmarks shows processing improvements with speedups above 2x with respect to baseline, non-streamed GPU execution.